React Jobs
152 jobs found
LawnStarter
2 days ago
This is a remote role for candidates located in Porto Alegre, Brazil. About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services — operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Engineering at LawnStarter We're restructuring engineering around initiative teams: a Product Engineer paired with a PM and a designer, with an Engineering Manager who covers a couple of initiatives and supports your growth. The engineer leads AI agents like a team, ships the work, and is accountable — with the rest of the triangle — for whether the initiative moves its metric. We're betting that 1–2 strong engineers running AI agents can outship the labor-team model that defined the last decade of software. That bet only works if the engineers we hire are wired for ownership and can ship to a marketplace with real customers and pros on both sides. The Role You're the engineering anchor of one initiative at a time. The initiative is a team effort — an iron triangle of you, your PM, and your designer — and you have key participation across the full lifecycle: shaping the problem, deciding the technical approach, leading the AI agents that implement most of the code, shipping to production, and answering for the outcome alongside the rest of the triangle. You're accountable for the outcome — not for the volume of code merged. If an agent can ship it safely, your job is to make sure the agent does it right and the metric moves. If the initiative needs hand-written code in a sensitive area, you write it yourself. What makes this role different: You lead AI agents, not humans. Claude Code, Cursor, Codex, and our internal agent stack are your team. You own the quality, safety, and velocity of what they produce. You own an outcome, not a ticket queue. Problem-framing through production through the metric review 2–4 weeks after launch. You partner horizontally with PM and design. No tech lead above you. No architect approval. No ticket grooming committee. The bar is staff, not senior. You make the call when the call needs to be made. If you're waiting to be told, this isn't the role. What You'll Own The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make the call, document it, and revisit it if the data says you were wrong. Agent-led implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code on your initiative. Most lines will be agent-authored. You're accountable for them. Cross-functional partnership — daily working contact with your PM (scope, tradeoffs) and your designer (UX decisions, in-tool prototyping with agents), and weekly check-ins with your EM (initiative health, blockers, growth). The initiative outcome — the specific metric the initiative was set up to move. In partnership with your PM, you present results 2–4 weeks post-launch and share the "did it work" answer. A high bar for what ships under your name — production correctness, security posture, performance, observability, and the experience for customers and pros. Agents accelerate you; they don't lower the bar. Problems to Solve Leading AI agents at staff-level qualityMost of the code on your initiative will be authored by AI agents. The work is making agents ship as if a senior engineer wrote it: prompts that encode our codebase conventions, evals that catch hallucinations before merge, tests that exercise the edges, observability that catches the regression in production before a customer reports it. How do you build the agent workflow that lets one engineer ship what used to take a team? Owning an outcome without a tech leadYou don't have a tech lead to approve your design or an architect to escalate to. You have an EM who covers a couple of initiatives and peers on adjacent ones. How do you make calls fast, document them clearly, and stay accountable to the outcome — without slowing down for hierarchy that no longer exists? Shipping outcomes, not featuresThe initiative will be measured by a metric — a conversion rate, a retention curve, a pro-funnel KPI, a unit economics shift. You're accountable for the number, not the feature. How do you scope to actually move it, decide what to not build, and have the discipline to follow up 2–4 weeks after launch even when the next initiative is calling? What Success Looks Like (Year 1) Initiative outcomes hit — You've shipped 3–4 initiatives end-to-end, and at least two clearly moved the metric they were set up to move (with the post-launch review to prove it). Agent workflow that travels — The prompts, evals, and review loop you built for your initiative are adopted by at least one other engineer on an adjacent initiative. Cycle time — Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter than the pre-restructure baseline. Zero "agent-shipped that" incidents — No customer- or pro-facing regression traceable to agent-authored code that you missed in review. Visible leverage — Other engineers point to artifacts you left behind — runbooks, evals, agent workflows, post-launch write-ups — as references they use. Who You Are AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship — daily, on production work. You have opinions about prompts, evals, agent loops, MCP servers, and review workflows, and you know when to let the agent run vs. write it yourself. This is unlikely to be a good fit if you describe AI coding as "something you're exploring" or prefer to write everything by hand. Already operating at lead level. You may currently be titled Senior, Staff, Lead, or Principal — but in practice you've been the person making the call, shipping the hard thing, and answering for whether it worked. This is unlikely to be a good fit if you've always had a tech lead breaking down the work for you. Outcome-driven, not output-driven. You measure your week in "did the metric move" and "did the experience get better," not in tickets closed. You read the post-launch dashboard and you own the answer. This is unlikely to be a good fit if you take pride in volume of code shipped or feel uncomfortable being measured on a number you don't fully control. A strong horizontal partner. You hold your own with a strong PM and a strong designer. You bring engineering judgment to product calls and product judgment to engineering calls. This is unlikely to be a good fit if you hide behind "that's product's decision" or default to RICE-scoring tickets handed down to you. Decisive and documented. Architecture decisions, data-model choices, rollout plans — you write them down, get fast input, and move. This is unlikely to be a good fit if you wait for consensus on questions that have a clear right answer, or if you make calls and never write them down. Raises the floor, not just the ceiling. Your impact compounds beyond your own initiative because you leave artifacts — agent workflows, evals, runbooks, post-launch reviews. This is unlikely to be a good fit if you're a lone wolf who ships brilliantly but leaves nothing reusable behind. Cares about customers and pros. This is a real-world marketplace with real people on both sides. This is unlikely to be a good fit if you're chasing pure engineering elegance over business and customer outcomes. This Role Is NOT A tech lead in an old-style team. No 4–5 engineers reporting up to you on technical direction. The team is you + PM + designer + EM, with AI agents doing most of the implementation. A management role today. People management is the EM's job in this role. That said, the path can grow into management for those who want it — it's an open door, not a closed one. A platform-only or architecture-only role. You're a Product Engineer. You ship features that move metrics, end-to-end. Platform work happens inside the initiative when it's needed for the outcome. A "let AI do everything" role. Agents handle implementation grunt work. You handle judgment, design, safety, and accountability. The bar is higher than the old senior bar, not lower. A research role. This is shipping to a marketplace with $100M+ in bookings. Customers and pros are using what you ship inside the same week. Tech You'll Touch AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling Backend — PHP/Laravel Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile) Data — Redshift, dbt, Segment, Airflow Infra — AWS, Datadog, Sentry, GitHub Actions Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents. Benefits Competitive salary of USD $80,000–$100,000 annual base Work from anywhere High ownership and autonomy Fast-moving team that loves to build, learn, and grow
LawnStarter
2 days ago
This is a remote role for candidates located in Belo Horizonte, Brazil. About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services — operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Engineering at LawnStarter We're restructuring engineering around initiative teams: a Product Engineer paired with a PM and a designer, with an Engineering Manager who covers a couple of initiatives and supports your growth. The engineer leads AI agents like a team, ships the work, and is accountable — with the rest of the triangle — for whether the initiative moves its metric. We're betting that 1–2 strong engineers running AI agents can outship the labor-team model that defined the last decade of software. That bet only works if the engineers we hire are wired for ownership and can ship to a marketplace with real customers and pros on both sides. The Role You're the engineering anchor of one initiative at a time. The initiative is a team effort — an iron triangle of you, your PM, and your designer — and you have key participation across the full lifecycle: shaping the problem, deciding the technical approach, leading the AI agents that implement most of the code, shipping to production, and answering for the outcome alongside the rest of the triangle. You're accountable for the outcome — not for the volume of code merged. If an agent can ship it safely, your job is to make sure the agent does it right and the metric moves. If the initiative needs hand-written code in a sensitive area, you write it yourself. What makes this role different: You lead AI agents, not humans. Claude Code, Cursor, Codex, and our internal agent stack are your team. You own the quality, safety, and velocity of what they produce. You own an outcome, not a ticket queue. Problem-framing through production through the metric review 2–4 weeks after launch. You partner horizontally with PM and design. No tech lead above you. No architect approval. No ticket grooming committee. The bar is staff, not senior. You make the call when the call needs to be made. If you're waiting to be told, this isn't the role. What You'll Own The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make the call, document it, and revisit it if the data says you were wrong. Agent-led implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code on your initiative. Most lines will be agent-authored. You're accountable for them. Cross-functional partnership — daily working contact with your PM (scope, tradeoffs) and your designer (UX decisions, in-tool prototyping with agents), and weekly check-ins with your EM (initiative health, blockers, growth). The initiative outcome — the specific metric the initiative was set up to move. In partnership with your PM, you present results 2–4 weeks post-launch and share the "did it work" answer. A high bar for what ships under your name — production correctness, security posture, performance, observability, and the experience for customers and pros. Agents accelerate you; they don't lower the bar. Problems to Solve Leading AI agents at staff-level qualityMost of the code on your initiative will be authored by AI agents. The work is making agents ship as if a senior engineer wrote it: prompts that encode our codebase conventions, evals that catch hallucinations before merge, tests that exercise the edges, observability that catches the regression in production before a customer reports it. How do you build the agent workflow that lets one engineer ship what used to take a team? Owning an outcome without a tech leadYou don't have a tech lead to approve your design or an architect to escalate to. You have an EM who covers a couple of initiatives and peers on adjacent ones. How do you make calls fast, document them clearly, and stay accountable to the outcome — without slowing down for hierarchy that no longer exists? Shipping outcomes, not featuresThe initiative will be measured by a metric — a conversion rate, a retention curve, a pro-funnel KPI, a unit economics shift. You're accountable for the number, not the feature. How do you scope to actually move it, decide what to not build, and have the discipline to follow up 2–4 weeks after launch even when the next initiative is calling? What Success Looks Like (Year 1) Initiative outcomes hit — You've shipped 3–4 initiatives end-to-end, and at least two clearly moved the metric they were set up to move (with the post-launch review to prove it). Agent workflow that travels — The prompts, evals, and review loop you built for your initiative are adopted by at least one other engineer on an adjacent initiative. Cycle time — Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter than the pre-restructure baseline. Zero "agent-shipped that" incidents — No customer- or pro-facing regression traceable to agent-authored code that you missed in review. Visible leverage — Other engineers point to artifacts you left behind — runbooks, evals, agent workflows, post-launch write-ups — as references they use. Who You Are AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship — daily, on production work. You have opinions about prompts, evals, agent loops, MCP servers, and review workflows, and you know when to let the agent run vs. write it yourself. This is unlikely to be a good fit if you describe AI coding as "something you're exploring" or prefer to write everything by hand. Already operating at lead level. You may currently be titled Senior, Staff, Lead, or Principal — but in practice you've been the person making the call, shipping the hard thing, and answering for whether it worked. This is unlikely to be a good fit if you've always had a tech lead breaking down the work for you. Outcome-driven, not output-driven. You measure your week in "did the metric move" and "did the experience get better," not in tickets closed. You read the post-launch dashboard and you own the answer. This is unlikely to be a good fit if you take pride in volume of code shipped or feel uncomfortable being measured on a number you don't fully control. A strong horizontal partner. You hold your own with a strong PM and a strong designer. You bring engineering judgment to product calls and product judgment to engineering calls. This is unlikely to be a good fit if you hide behind "that's product's decision" or default to RICE-scoring tickets handed down to you. Decisive and documented. Architecture decisions, data-model choices, rollout plans — you write them down, get fast input, and move. This is unlikely to be a good fit if you wait for consensus on questions that have a clear right answer, or if you make calls and never write them down. Raises the floor, not just the ceiling. Your impact compounds beyond your own initiative because you leave artifacts — agent workflows, evals, runbooks, post-launch reviews. This is unlikely to be a good fit if you're a lone wolf who ships brilliantly but leaves nothing reusable behind. Cares about customers and pros. This is a real-world marketplace with real people on both sides. This is unlikely to be a good fit if you're chasing pure engineering elegance over business and customer outcomes. This Role Is NOT A tech lead in an old-style team. No 4–5 engineers reporting up to you on technical direction. The team is you + PM + designer + EM, with AI agents doing most of the implementation. A management role today. People management is the EM's job in this role. That said, the path can grow into management for those who want it — it's an open door, not a closed one. A platform-only or architecture-only role. You're a Product Engineer. You ship features that move metrics, end-to-end. Platform work happens inside the initiative when it's needed for the outcome. A "let AI do everything" role. Agents handle implementation grunt work. You handle judgment, design, safety, and accountability. The bar is higher than the old senior bar, not lower. A research role. This is shipping to a marketplace with $100M+ in bookings. Customers and pros are using what you ship inside the same week. Tech You'll Touch AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling Backend — PHP/Laravel Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile) Data — Redshift, dbt, Segment, Airflow Infra — AWS, Datadog, Sentry, GitHub Actions Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents. Benefits Competitive salary of USD $80,000–$100,000 annual base Work from anywhere High ownership and autonomy Fast-moving team that loves to build, learn, and grow
LawnStarter
2 days ago
This is a remote role for candidates located in Florianópolis, Brazil About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services — operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Engineering at LawnStarter We're restructuring engineering around initiative teams: a Product Engineer paired with a PM and a designer, with an Engineering Manager who covers a couple of initiatives and supports your growth. The engineer leads AI agents like a team, ships the work, and is accountable — with the rest of the triangle — for whether the initiative moves its metric. We're betting that 1–2 strong engineers running AI agents can outship the labor-team model that defined the last decade of software. That bet only works if the engineers we hire are wired for ownership and can ship to a marketplace with real customers and pros on both sides. The Role You're the engineering anchor of one initiative at a time. The initiative is a team effort — an iron triangle of you, your PM, and your designer — and you have key participation across the full lifecycle: shaping the problem, deciding the technical approach, leading the AI agents that implement most of the code, shipping to production, and answering for the outcome alongside the rest of the triangle. You're accountable for the outcome — not for the volume of code merged. If an agent can ship it safely, your job is to make sure the agent does it right and the metric moves. If the initiative needs hand-written code in a sensitive area, you write it yourself. What makes this role different: You lead AI agents, not humans. Claude Code, Cursor, Codex, and our internal agent stack are your team. You own the quality, safety, and velocity of what they produce. You own an outcome, not a ticket queue. Problem-framing through production through the metric review 2–4 weeks after launch. You partner horizontally with PM and design. No tech lead above you. No architect approval. No ticket grooming committee. The bar is staff, not senior. You make the call when the call needs to be made. If you're waiting to be told, this isn't the role. What You'll Own The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make the call, document it, and revisit it if the data says you were wrong. Agent-led implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code on your initiative. Most lines will be agent-authored. You're accountable for them. Cross-functional partnership — daily working contact with your PM (scope, tradeoffs) and your designer (UX decisions, in-tool prototyping with agents), and weekly check-ins with your EM (initiative health, blockers, growth). The initiative outcome — the specific metric the initiative was set up to move. In partnership with your PM, you present results 2–4 weeks post-launch and share the "did it work" answer. A high bar for what ships under your name — production correctness, security posture, performance, observability, and the experience for customers and pros. Agents accelerate you; they don't lower the bar. Problems to Solve Leading AI agents at staff-level qualityMost of the code on your initiative will be authored by AI agents. The work is making agents ship as if a senior engineer wrote it: prompts that encode our codebase conventions, evals that catch hallucinations before merge, tests that exercise the edges, observability that catches the regression in production before a customer reports it. How do you build the agent workflow that lets one engineer ship what used to take a team? Owning an outcome without a tech leadYou don't have a tech lead to approve your design or an architect to escalate to. You have an EM who covers a couple of initiatives and peers on adjacent ones. How do you make calls fast, document them clearly, and stay accountable to the outcome — without slowing down for hierarchy that no longer exists? Shipping outcomes, not featuresThe initiative will be measured by a metric — a conversion rate, a retention curve, a pro-funnel KPI, a unit economics shift. You're accountable for the number, not the feature. How do you scope to actually move it, decide what to not build, and have the discipline to follow up 2–4 weeks after launch even when the next initiative is calling? What Success Looks Like (Year 1) Initiative outcomes hit — You've shipped 3–4 initiatives end-to-end, and at least two clearly moved the metric they were set up to move (with the post-launch review to prove it). Agent workflow that travels — The prompts, evals, and review loop you built for your initiative are adopted by at least one other engineer on an adjacent initiative. Cycle time — Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter than the pre-restructure baseline. Zero "agent-shipped that" incidents — No customer- or pro-facing regression traceable to agent-authored code that you missed in review. Visible leverage — Other engineers point to artifacts you left behind — runbooks, evals, agent workflows, post-launch write-ups — as references they use. Who You Are AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship — daily, on production work. You have opinions about prompts, evals, agent loops, MCP servers, and review workflows, and you know when to let the agent run vs. write it yourself. This is unlikely to be a good fit if you describe AI coding as "something you're exploring" or prefer to write everything by hand. Already operating at lead level. You may currently be titled Senior, Staff, Lead, or Principal — but in practice you've been the person making the call, shipping the hard thing, and answering for whether it worked. This is unlikely to be a good fit if you've always had a tech lead breaking down the work for you. Outcome-driven, not output-driven. You measure your week in "did the metric move" and "did the experience get better," not in tickets closed. You read the post-launch dashboard and you own the answer. This is unlikely to be a good fit if you take pride in volume of code shipped or feel uncomfortable being measured on a number you don't fully control. A strong horizontal partner. You hold your own with a strong PM and a strong designer. You bring engineering judgment to product calls and product judgment to engineering calls. This is unlikely to be a good fit if you hide behind "that's product's decision" or default to RICE-scoring tickets handed down to you. Decisive and documented. Architecture decisions, data-model choices, rollout plans — you write them down, get fast input, and move. This is unlikely to be a good fit if you wait for consensus on questions that have a clear right answer, or if you make calls and never write them down. Raises the floor, not just the ceiling. Your impact compounds beyond your own initiative because you leave artifacts — agent workflows, evals, runbooks, post-launch reviews. This is unlikely to be a good fit if you're a lone wolf who ships brilliantly but leaves nothing reusable behind. Cares about customers and pros. This is a real-world marketplace with real people on both sides. This is unlikely to be a good fit if you're chasing pure engineering elegance over business and customer outcomes. This Role Is NOT A tech lead in an old-style team. No 4–5 engineers reporting up to you on technical direction. The team is you + PM + designer + EM, with AI agents doing most of the implementation. A management role today. People management is the EM's job in this role. That said, the path can grow into management for those who want it — it's an open door, not a closed one. A platform-only or architecture-only role. You're a Product Engineer. You ship features that move metrics, end-to-end. Platform work happens inside the initiative when it's needed for the outcome. A "let AI do everything" role. Agents handle implementation grunt work. You handle judgment, design, safety, and accountability. The bar is higher than the old senior bar, not lower. A research role. This is shipping to a marketplace with $100M+ in bookings. Customers and pros are using what you ship inside the same week. Tech You'll Touch AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling Backend — PHP/Laravel Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile) Data — Redshift, dbt, Segment, Airflow Infra — AWS, Datadog, Sentry, GitHub Actions Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents. Benefits Competitive salary of USD $80,000–$100,000 annual base Work from anywhere High ownership and autonomy Fast-moving team that loves to build, learn, and grow
LawnStarter
3 days ago
This is a remote role for candidates located in Campinas, Brazil. About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services — operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Engineering at LawnStarter We're restructuring engineering around initiative teams: a Product Engineer paired with a PM and a designer, with an Engineering Manager who covers a couple of initiatives and supports your growth. The engineer leads AI agents like a team, ships the work, and is accountable — with the rest of the triangle — for whether the initiative moves its metric. We're betting that 1–2 strong engineers running AI agents can outship the labor-team model that defined the last decade of software. That bet only works if the engineers we hire are wired for ownership and can ship to a marketplace with real customers and pros on both sides. The Role You're the engineering anchor of one initiative at a time. The initiative is a team effort — an iron triangle of you, your PM, and your designer — and you have key participation across the full lifecycle: shaping the problem, deciding the technical approach, leading the AI agents that implement most of the code, shipping to production, and answering for the outcome alongside the rest of the triangle. You're accountable for the outcome — not for the volume of code merged. If an agent can ship it safely, your job is to make sure the agent does it right and the metric moves. If the initiative needs hand-written code in a sensitive area, you write it yourself. What makes this role different: You lead AI agents, not humans. Claude Code, Cursor, Codex, and our internal agent stack are your team. You own the quality, safety, and velocity of what they produce. You own an outcome, not a ticket queue. Problem-framing through production through the metric review 2–4 weeks after launch. You partner horizontally with PM and design. No tech lead above you. No architect approval. No ticket grooming committee. The bar is staff, not senior. You make the call when the call needs to be made. If you're waiting to be told, this isn't the role. What You'll Own The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make the call, document it, and revisit it if the data says you were wrong. Agent-led implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code on your initiative. Most lines will be agent-authored. You're accountable for them. Cross-functional partnership — daily working contact with your PM (scope, tradeoffs) and your designer (UX decisions, in-tool prototyping with agents), and weekly check-ins with your EM (initiative health, blockers, growth). The initiative outcome — the specific metric the initiative was set up to move. In partnership with your PM, you present results 2–4 weeks post-launch and share the "did it work" answer. A high bar for what ships under your name — production correctness, security posture, performance, observability, and the experience for customers and pros. Agents accelerate you; they don't lower the bar. Problems to Solve Leading AI agents at staff-level qualityMost of the code on your initiative will be authored by AI agents. The work is making agents ship as if a senior engineer wrote it: prompts that encode our codebase conventions, evals that catch hallucinations before merge, tests that exercise the edges, observability that catches the regression in production before a customer reports it. How do you build the agent workflow that lets one engineer ship what used to take a team? Owning an outcome without a tech leadYou don't have a tech lead to approve your design or an architect to escalate to. You have an EM who covers a couple of initiatives and peers on adjacent ones. How do you make calls fast, document them clearly, and stay accountable to the outcome — without slowing down for hierarchy that no longer exists? Shipping outcomes, not featuresThe initiative will be measured by a metric — a conversion rate, a retention curve, a pro-funnel KPI, a unit economics shift. You're accountable for the number, not the feature. How do you scope to actually move it, decide what to not build, and have the discipline to follow up 2–4 weeks after launch even when the next initiative is calling? What Success Looks Like (Year 1) Initiative outcomes hit — You've shipped 3–4 initiatives end-to-end, and at least two clearly moved the metric they were set up to move (with the post-launch review to prove it). Agent workflow that travels — The prompts, evals, and review loop you built for your initiative are adopted by at least one other engineer on an adjacent initiative. Cycle time — Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter than the pre-restructure baseline. Zero "agent-shipped that" incidents — No customer- or pro-facing regression traceable to agent-authored code that you missed in review. Visible leverage — Other engineers point to artifacts you left behind — runbooks, evals, agent workflows, post-launch write-ups — as references they use. Who You Are AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship — daily, on production work. You have opinions about prompts, evals, agent loops, MCP servers, and review workflows, and you know when to let the agent run vs. write it yourself. This is unlikely to be a good fit if you describe AI coding as "something you're exploring" or prefer to write everything by hand. Already operating at lead level. You may currently be titled Senior, Staff, Lead, or Principal — but in practice you've been the person making the call, shipping the hard thing, and answering for whether it worked. This is unlikely to be a good fit if you've always had a tech lead breaking down the work for you. Outcome-driven, not output-driven. You measure your week in "did the metric move" and "did the experience get better," not in tickets closed. You read the post-launch dashboard and you own the answer. This is unlikely to be a good fit if you take pride in volume of code shipped or feel uncomfortable being measured on a number you don't fully control. A strong horizontal partner. You hold your own with a strong PM and a strong designer. You bring engineering judgment to product calls and product judgment to engineering calls. This is unlikely to be a good fit if you hide behind "that's product's decision" or default to RICE-scoring tickets handed down to you. Decisive and documented. Architecture decisions, data-model choices, rollout plans — you write them down, get fast input, and move. This is unlikely to be a good fit if you wait for consensus on questions that have a clear right answer, or if you make calls and never write them down. Raises the floor, not just the ceiling. Your impact compounds beyond your own initiative because you leave artifacts — agent workflows, evals, runbooks, post-launch reviews. This is unlikely to be a good fit if you're a lone wolf who ships brilliantly but leaves nothing reusable behind. Cares about customers and pros. This is a real-world marketplace with real people on both sides. This is unlikely to be a good fit if you're chasing pure engineering elegance over business and customer outcomes. This Role Is NOT A tech lead in an old-style team. No 4–5 engineers reporting up to you on technical direction. The team is you + PM + designer + EM, with AI agents doing most of the implementation. A management role today. People management is the EM's job in this role. That said, the path can grow into management for those who want it — it's an open door, not a closed one. A platform-only or architecture-only role. You're a Product Engineer. You ship features that move metrics, end-to-end. Platform work happens inside the initiative when it's needed for the outcome. A "let AI do everything" role. Agents handle implementation grunt work. You handle judgment, design, safety, and accountability. The bar is higher than the old senior bar, not lower. A research role. This is shipping to a marketplace with $100M+ in bookings. Customers and pros are using what you ship inside the same week. Tech You'll Touch AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling Backend — PHP/Laravel Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile) Data — Redshift, dbt, Segment, Airflow Infra — AWS, Datadog, Sentry, GitHub Actions Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents. Benefits Competitive salary of USD $80,000–$100,000 annual base Work from anywhere High ownership and autonomy Fast-moving team that loves to build, learn, and grow
4 days ago
## Building the Future of Crypto Our Krakenites are a world-class team with crypto conviction, united by our desire to discover and unlock the potential of crypto and blockchain technology. **What makes us different?** Kraken is a mission-focused company rooted in crypto values. As a Krakenite, you'll join us on our mission to accelerate the global adoption of crypto, so that everyone can achieve financial freedom and inclusion. For over a decade, Kraken's focus on our mission and crypto ethos has attracted many of the most talented crypto experts in the world. Before you apply, please read the **Kraken Culture** page to learn more about our internal culture, values, and mission. We also expect candidates to familiarize themselves with the Kraken app. Learn how to create a Kraken account here. As a fully remote company, we have Krakenites in 70+ countries who speak over 50 languages. Krakenites are industry pioneers who develop premium crypto products for experienced traders, institutions, and newcomers to the space. Kraken is committed to industry-leading security, crypto education, and world-class client support through our products like Kraken Pro, Desktop, Wallet, and Kraken Futures. **Become a Krakenite and build the future of crypto!** ## Proof of Work ### The Team We are currently seeking an experienced **Staff Software Engineer (React Native)** to join our **Pro Trading team**. The Pro team is responsible for Kraken Pro's web and mobile trading experiences across spot and futures markets. Distributed globally, the team builds and scales high-performance trading interfaces using Typescript and React, delivering fast, reliable, and intuitive experiences for advanced traders. Join the Pro team and help build the internet of money. You'll lead and grow a distributed team of engineers responsible for the frontend and mobile experience powering Kraken Pro. In this role, you'll drive technical direction, product execution, and engineering excellence across Kraken's next generation trading platform. ### The Opportunity - Own and drive the technical vision and architecture of Kraken's Pro mobile application - Build and maintain high-performance mobile applications using React Native and TypeScript - Lead initiatives to improve app performance, reliability, and scalability (e.g. startup time, responsiveness, resource efficiency) - Act as a technical leader across multiple teams, ensuring consistency and quality across a shared codebase - Partner with Product, Design, and Backend teams to deliver impactful, user-facing features - Take the lead during critical production issues, diagnosing problems and driving solutions - Define and evolve engineering standards, best practices, and tooling for mobile development - Mentor engineers and elevate the overall technical capability of the team - Stay close to the code while operating at a strategic, platform level ### Skills You Should HODL - 8+ years of experience in software engineering, with a strong focus on mobile development - Deep expertise in React Native and TypeScript - Proven experience owning or leading large-scale, production mobile applications - Strong understanding of mobile performance optimization, architecture, and debugging - Experience delivering measurable improvements to app performance (e.g. load time, stability, efficiency) - Solid knowledge of iOS and Android platforms - Experience working across multiple teams or shared platforms - Strong communication skills, with the ability to influence technical direction across teams - A proactive, ownership-driven mindset with a bias for action ### Nice to Haves - Significant experience developing micro interactions and animations in React Native - Experience building high-performance consumer or fintech applications - Familiarity with native mobile development (Swift, Kotlin, etc.) - Experience defining or scaling mobile platforms across multiple teams - Background in fast-growing or highly technical product environments - Contributions to open-source or the broader engineering community --- *Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.* *Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.* *We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.* Kraken is powered by people from around the world and we celebrate all Krakenites for their diverse talents, backgrounds, contributions and unique perspectives. We hire strictly based on merit, meaning we seek out the candidates with the right abilities, knowledge, and skills considered the most suitable for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto! We may ask candidates to complete job-related skills or work samples. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind. Whether that's based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws. **Stay in the know** - Follow us on Twitter - Learn on the Kraken Blog - Connect on LinkedIn - Candidate Privacy Notice *When applying, mention the word CANDYSHOP to show you read the job post completely.*
Fireblocks
8 days ago
## **Full Stack Engineer - Wallet Flows Team** The world of digital assets is accelerating in speed, magnitude, and complexity, opening the door to new ways for leveraging the blockchain. **Fireblocks'** platform and network provide the simplest and most secure way for companies to work with digital assets and is trusted by some of the largest financial institutions, banks, globally-recognized brands, and Web3 companies in the world, including BNY Mellon, BNP Paribas, ANZ Bank, Revolut, and thousands more. ### **About The Team** The **Wallet Flows** team is leading a strategic transformation of Fireblocks' core infrastructure. We're methodically redesigning and rewriting major system components to create next-generation architecture that enhances security, scalability, and performance. Our team blends industry veterans and rising talent, united by excellence and a results-driven mindset. We value seasoned expertise alongside fresh perspectives, fostering an environment where pragmatic solutions and innovation thrive together. ### **About The Role** We are looking for a **Full Stack Engineer** with a strong blockchain foundation. In this role, you will work across the entire stack — from user-facing interfaces to backend services and on-chain integrations — to build and evolve the systems that power institutional digital asset operations. You will serve as a technical bridge between raw blockchain capabilities and the polished wallet experiences delivered to customers. This means diving into protocol-level details one day and refining a transaction workflow UI the next. Your blockchain expertise will directly inform how we design, build, and ship features that handle billions in transaction volume. ### **What You'll Do** - Design and build end-to-end features across frontend, backend, and blockchain layers that power Fireblocks' wallet infrastructure - Architect and deliver mission-critical components while maintaining 24/7 operations with zero disruption to live transaction volume - Research and integrate blockchain technologies including Layer 2 solutions, cross-chain bridges, staking protocols, and DeFi integrations into the Fireblocks platform - Develop intuitive, responsive interfaces that surface complex blockchain operations in a clear and actionable way for institutional users - Collaborate with blockchain foundations, vendors, builders, and customers to understand protocol design, tooling, and integration requirements - Balance pragmatism with vision — make smart trade-offs to deliver incremental value while steadily advancing toward next-generation architecture goals - Collaborate with product, engineering, and security teams to define technical requirements and deliver cohesive solutions - Mentor and guide other engineers on blockchain technologies, full stack patterns, and best practices ### **What You'll Bring** - 5+ years of full stack development experience with modern frontend frameworks (**TypeScript**) and backend services (**Go**, or **Python**) - 3+ years of hands-on experience in the blockchain ecosystem — working with protocols, on-chain data, smart contracts, or wallet infrastructure - Knowledge of consensus mechanisms, cryptographic primitives, and distributed systems - Strong understanding of microservices architecture, API design, and modern frontend patterns - Demonstrated ability to apply AI tools for programming with experience in vibe coding - Strong verbal and written communication skills and a collaborative mindset - Experience working in cross-functional teams and fast-paced environments - A curious mind, willing to learn, including new coding languages and tech stacks ### **Preferred** - Experience building blockchain solutions for enterprise or institutional use cases - Understanding of security best practices for smart contracts and blockchain systems - Experience with MPC, multi-signature wallets, or other advanced cryptographic techniques - Experience with institutional DeFi, staking protocols, or custody solutions - Experience modernizing and transforming mission-critical production systems with minimal disruption - Bachelor's degree in Computer Science, Engineering, or related field; Master's degree preferred ### **Success Criteria & Impact** - You deliver features end-to-end — from UI to on-chain integration — with high quality and minimal iteration - Your blockchain expertise is consistently leveraged as a foundation for architectural and product decisions - You are considered a subject matter expert by internal engineering teams across both application and protocol layers - Consistent contribution to the Fireblocks platform by pushing impactful design and code to production ### **Compensation & Benefits** For employees hired to work from our NYC HQ, Fireblocks is required by law to include a reasonable estimate of the compensation range for this role. This range is specific to New York City, and takes into consideration a wide range of factors that are reviewed when making a hiring decision, such as years of experience, skills, and other business needs. It is not typical for a candidate to be hired at or near the top of the pay range and each compensation decision is dependent on each individual case. A reasonable base salary range estimate for this position is **$177,000 to $230,000**. The base salary is one component of the total compensation package, which for some roles may include a target bonus, a very competitive equity grant, and very generous benefits. While we believe competitive compensation is a critical aspect of you deciding to join us, we do hope you also spend time considering why our mission and culture are right for you. We are creating something transformational here, and we hope you are as excited about the future as we are. *Fireblocks' mission is to enable every business to easily and securely access digital assets and cryptocurrencies. In order to do that, we strongly believe our workforce should be as diverse as our clients, and this is why we embrace diversity and inclusion in all its forms.* *Please see our candidate privacy policy [here](https://www.fireblocks.com/candidate-privacy-policy/).* When applying, mention the word **CANDYSHOP** to show you read the job post completely.
Lemon.io
8 days ago
## Senior Blockchain Developer (Remote) Are you a talented **Senior Developer** looking for a remote job that lets you showcase your skills and earn competitive compensation? Look no further than **Lemon.io** — the marketplace that connects you with hand-picked startups in the US and Europe. ### What We Offer - The rate depends on your seniority level, skills, and experience. We've already paid out over **$11M** to our engineers. - No more hunting for clients or negotiating rates — let us handle the business side so you can focus on what you do best. - We'll manually find the best project for you according to your skills and preferences. - Choose a schedule that works best for you. It's possible to communicate async or minimally overlap within team working hours. - We respect your seniority — expect no micromanagement or screen trackers. - Communicate directly with the clients. Most of them have technical backgrounds. - We will support you from the time you submit the application throughout all cooperation stages. - Most of our projects involve working in a fast-paced startup environment. We hope you like it as much as we do. - Through our community, we will connect you with the best developers from more than **71 countries**. We are currently looking for **Senior Blockchain Developers** for different projects. ### Requirements – Senior Blockchain Developer with Ethereum/Ethers/Web3 - 4+ years of software development experience. - 3+ years of Ethereum ecosystem expertise, **Ethers.js** or **Web3.js** (required). - Experience with **React** and **Node.js**, including at least 2 commercial projects. ### Requirements – Senior Blockchain Developer with Solana - 4+ years of software development experience. - 2+ years of expertise in **Solana** (required). - Experience with **Smart contracts** is a must. ### Other Requirements - **Strong technical skills:** As a Senior Developer, you are expected to be able to create projects from scratch and have a deep understanding of application architecture. - **Clear and effective communication in English** — advanced ability to discuss business tasks, justify decisions, and communicate issues. Good self-presentation is also essential for upcoming client calls. - **Strong self-organizational skills** — ability to work full-time remotely with no supervision. - **Reliability** — we want to trust you and expect that you won't let us or the client down. - **Adaptability and flexibility** — the ability to onboard the project promptly after accepting it and start delivering results quickly. ### Other Opportunities We have different projects for **Senior Full-Stack Developers**. If you have 4+ years of commercial experience in software development and you are fluent with any of the following, we would be happy to communicate and provide you with a project that matches your experience: - AI Agent Architect - AI Automation Architect - React & Python - React & Golang - React & Java - React & Ruby - PHP & Vue - Vue & Node.js - React & .NET - Android & iOS - Angular & Node.js - Vue & .NET - Python & Vue - DevOps with Azure DevOps - MLOps - Data Science - Angular & PHP - Angular & .NET - Symfony & React - Symfony & Vue - Symfony & Angular - Symfony & JavaScript & Next.js & TypeScript - Data Analysis - React & PHP - Data Engineering - AI Engineering - Data Annotation - React & Node - Svelte & Python - Svelte & Node - Svelte & TypeScript - Rust - Shopify & JavaScript - Vue & Nuxt - PHP & Laravel - .NET & C# - Unreal Engine & C++ - Python & LLM - Unity - Machine Learning Engineering Just apply, and we will share more details with you. ### Important Notes - We do not provide visa assistance, and our cooperation model does not include the benefits typically offered with direct hire. - We work with developers from **75+ countries** across different regions: Europe, LATAM, the U.S. (if you have a completed W-9 form), Canada, Asia (Japan, Singapore, South Korea, the Philippines, Indonesia, Malaysia, Vietnam, Thailand, South Africa, and Israel), Oceania (Australia, New Zealand, and Papua New Guinea), Morocco, and the UK. However, there are some exceptions. **At the moment, we don't have a legal basis to accept applicants from the following countries:** - **European:** Hungary, Iceland, Liechtenstein, Kosovo, Belarus, Russia, and Serbia. - **Latin America:** Cuba and Nicaragua. - Most Asian countries and Africa. We expand and shorten the list of exemptions regularly. --- *When applying, mention the word **CANDYSHOP** to show you read the job post completely.*
LawnStarter
8 days ago
About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services — operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform. About Engineering at LawnStarter We're restructuring engineering around initiative teams: a Product Engineer paired with a PM and a designer, with an Engineering Manager who covers a couple of initiatives and supports your growth. The engineer leads AI agents like a team, ships the work, and is accountable — with the rest of the triangle — for whether the initiative moves its metric. We're betting that 1–2 strong engineers running AI agents can outship the labor-team model that defined the last decade of software. That bet only works if the engineers we hire are wired for ownership and can ship to a marketplace with real customers and pros on both sides. The Role You're the engineering anchor of one initiative at a time. The initiative is a team effort — an iron triangle of you, your PM, and your designer — and you have key participation across the full lifecycle: shaping the problem, deciding the technical approach, leading the AI agents that implement most of the code, shipping to production, and answering for the outcome alongside the rest of the triangle. You're accountable for the outcome — not for the volume of code merged. If an agent can ship it safely, your job is to make sure the agent does it right and the metric moves. If the initiative needs hand-written code in a sensitive area, you write it yourself. What makes this role different: You lead AI agents, not humans. Claude Code, Cursor, Codex, and our internal agent stack are your team. You own the quality, safety, and velocity of what they produce. You own an outcome, not a ticket queue. Problem-framing through production through the metric review 2–4 weeks after launch. You partner horizontally with PM and design. No tech lead above you. No architect approval. No ticket grooming committee. The bar is staff, not senior. You make the call when the call needs to be made. If you're waiting to be told, this isn't the role. What You'll Own The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative. You make the call, document it, and revisit it if the data says you were wrong. Agent-led implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production-ready code on your initiative. Most lines will be agent-authored. You're accountable for them. Cross-functional partnership — daily working contact with your PM (scope, tradeoffs) and your designer (UX decisions, in-tool prototyping with agents), and weekly check-ins with your EM (initiative health, blockers, growth). The initiative outcome — the specific metric the initiative was set up to move. In partnership with your PM, you present results 2–4 weeks post-launch and share the "did it work" answer. A high bar for what ships under your name — production correctness, security posture, performance, observability, and the experience for customers and pros. Agents accelerate you; they don't lower the bar. Problems to Solve Leading AI agents at staff-level qualityMost of the code on your initiative will be authored by AI agents. The work is making agents ship as if a senior engineer wrote it: prompts that encode our codebase conventions, evals that catch hallucinations before merge, tests that exercise the edges, observability that catches the regression in production before a customer reports it. How do you build the agent workflow that lets one engineer ship what used to take a team? Owning an outcome without a tech leadYou don't have a tech lead to approve your design or an architect to escalate to. You have an EM who covers a couple of initiatives and peers on adjacent ones. How do you make calls fast, document them clearly, and stay accountable to the outcome — without slowing down for hierarchy that no longer exists? Shipping outcomes, not featuresThe initiative will be measured by a metric — a conversion rate, a retention curve, a pro-funnel KPI, a unit economics shift. You're accountable for the number, not the feature. How do you scope to actually move it, decide what to not build, and have the discipline to follow up 2–4 weeks after launch even when the next initiative is calling? What Success Looks Like (Year 1) Initiative outcomes hit — You've shipped 3–4 initiatives end-to-end, and at least two clearly moved the metric they were set up to move (with the post-launch review to prove it). Agent workflow that travels — The prompts, evals, and review loop you built for your initiative are adopted by at least one other engineer on an adjacent initiative. Cycle time — Median time from problem-framing to first production rollout on your initiatives is meaningfully shorter than the pre-restructure baseline. Zero "agent-shipped that" incidents — No customer- or pro-facing regression traceable to agent-authored code that you missed in review. Visible leverage — Other engineers point to artifacts you left behind — runbooks, evals, agent workflows, post-launch write-ups — as references they use. Who You Are AI-native. Claude Code, Cursor, Codex, or equivalent are how you ship — daily, on production work. You have opinions about prompts, evals, agent loops, MCP servers, and review workflows, and you know when to let the agent run vs. write it yourself. This is unlikely to be a good fit if you describe AI coding as "something you're exploring" or prefer to write everything by hand. Already operating at lead level. You may currently be titled Senior, Staff, Lead, or Principal — but in practice you've been the person making the call, shipping the hard thing, and answering for whether it worked. This is unlikely to be a good fit if you've always had a tech lead breaking down the work for you. Outcome-driven, not output-driven. You measure your week in "did the metric move" and "did the experience get better," not in tickets closed. You read the post-launch dashboard and you own the answer. This is unlikely to be a good fit if you take pride in volume of code shipped or feel uncomfortable being measured on a number you don't fully control. A strong horizontal partner. You hold your own with a strong PM and a strong designer. You bring engineering judgment to product calls and product judgment to engineering calls. This is unlikely to be a good fit if you hide behind "that's product's decision" or default to RICE-scoring tickets handed down to you. Decisive and documented. Architecture decisions, data-model choices, rollout plans — you write them down, get fast input, and move. This is unlikely to be a good fit if you wait for consensus on questions that have a clear right answer, or if you make calls and never write them down. Raises the floor, not just the ceiling. Your impact compounds beyond your own initiative because you leave artifacts — agent workflows, evals, runbooks, post-launch reviews. This is unlikely to be a good fit if you're a lone wolf who ships brilliantly but leaves nothing reusable behind. Cares about customers and pros. This is a real-world marketplace with real people on both sides. This is unlikely to be a good fit if you're chasing pure engineering elegance over business and customer outcomes. This Role Is NOT A tech lead in an old-style team. No 4–5 engineers reporting up to you on technical direction. The team is you + PM + designer + EM, with AI agents doing most of the implementation. A management role today. People management is the EM's job in this role. That said, the path can grow into management for those who want it — it's an open door, not a closed one. A platform-only or architecture-only role. You're a Product Engineer. You ship features that move metrics, end-to-end. Platform work happens inside the initiative when it's needed for the outcome. A "let AI do everything" role. Agents handle implementation grunt work. You handle judgment, design, safety, and accountability. The bar is higher than the old senior bar, not lower. A research role. This is shipping to a marketplace with $100M+ in bookings. Customers and pros are using what you ship inside the same week. Tech You'll Touch AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling Backend — PHP/Laravel Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile) Data — Redshift, dbt, Segment, Airflow Infra — AWS, Datadog, Sentry, GitHub Actions Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira You don't need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents. Benefits Competitive salary of USD $80,000–$100,000 annual base Work from anywhere High ownership and autonomy Fast-moving team that loves to build, learn, and grow
OpenZeppelin
9 days ago
## Application Instructions When applying, please mention the word **CANDYSHOP** to show you have read the job post completely.
Cryptio
9 days ago
## About Cryptio Cryptio is the leading **enterprise-grade financial data transformation and digital asset ERP platform** for accounting, financial reporting, tokenization compliance, and loan management solutions. It is a complete back and middle-office platform that delivers financial integrity and accountability for businesses in crypto. Its platform allows users to transform on-chain and off-chain crypto activity into auditable records for accounting, treasury, tax filings, license applications, loans activity, and regulatory reporting. Having recently announced our **$45m series B**, now couldn't be a better time to join! ## About the role We're hiring our first Applied AI Engineer to work directly with our Advisory Intelligence Product Engineer and the VP of Advisory Intelligence on net-new product. You'll have full-stack ownership from Postgres schema to React UI, and you'll collaborate directly with the VP on prompt architecture, workflow design, and product roadmap. The team is small on purpose. This is a high-autonomy seat with real room to grow. You'll experiment, ship, and shape the toolkit's direction. As the practice scales, the right person grows into a technical leader for the function. ## What you'll do The Advisory Intelligence toolkit covers the full accounting workflow: transaction-level close processes, chart of accounts benchmarking, policy generation, fit-gap analysis against institutional standards, and financial reporting outputs. Each tool combines deterministic logic (the parts where being wrong has financial consequences) with AI layers that draw on a structured library of real client engagements. You'll work across the suite with primary ownership on net-new builds. - Collaborate directly with the VP on prompt architecture, workflow design, and product roadmap. You're a builder who shapes what gets built. - Own full-stack feature delivery from Postgres schema through API layer through React UI - Build and maintain multi-step AI pipelines: prompt chaining, structured output parsing, confidence scoring, failure recovery, and audit-trail logging - Integrate third-party financial data APIs into production tool workflows - Build financial document ingestion: parse uploaded spreadsheets and structured reports into typed data models for downstream AI processing - Maintain and extend the deterministic pre-processing and heuristic layers that make AI output reliable enough for audit - Contribute to the AI output evaluation framework: structured test inputs, expected outputs, scoring rubrics - Work cross-functionally with finance practitioners, product, design, and leadership to scope what gets built and push back on specs that miss ## What you'll bring ### Core engineering - Production full-stack TypeScript: shipped real systems, not side projects - Strong Node.js backend: REST APIs, middleware auth, async pipelines with batching, concurrency limits, retries, timeouts - React and TypeScript for complex UI: state management with Zustand, schema validation with Zod, views that stay responsive at scale - Exposure to distributed systems and microservice architectures: you understand the failure modes (partial writes, retries, ordering, observability) even if you haven't owned a microservice deployment end-to-end ### Data and Postgres - Strong Postgres: data modeling for workflow and run-oriented schemas, indexing strategy, query troubleshooting at table scale - Experience designing versioned config and audit-trail schemas. Append-only matters in compliance contexts and you've built for it. ### How you operate - Strong communicator, written and verbal. You can explain a technical decision to a finance practitioner and a product spec back to engineering. - You take initiative. When the spec is wrong, you propose alternatives. When something's broken, you don't wait to be asked. - You work cross-functionally without friction. Finance, product, design, leadership are all on your week, not just other engineers. - Comfortable owning a feature from schema to UI without handoffs ## Bonus points - Hands-on production LLM work with AWS Bedrock, OpenAI, or the Anthropic SDK at real throughput - Multi-step prompt workflows: chaining, structured output extraction, confidence thresholds, graceful degradation - Debugged AI in production. You know where prompt issues end and infrastructure issues begin. - Next.js App Router experience: API routes, SSR in data-dense interfaces - Background job infrastructure for AI workflows (BullMQ, pg-boss, or similar) - Finance or accounting tooling experience. Familiarity with GAAP/IFRS, month-end close, or audit process is a real advantage. - AWS deployments, Docker, CI/CD pipeline ownership - Logging, monitoring, and production debugging in distributed systems - Parsing financial document formats (Excel, structured CSV, ERP exports) into typed pipelines ## Perks - 👩💻 Remote or Hybrid working - 🏝️ 25 days paid holiday plus bank holidays - 🙌 One additional day of annual leave each year, up to 30 total days - 🎂 Your birth off - 🧘 Mental health resources, wellbeing programs, and professional coaching - 🫶 Family-friendly policies - 💪 Fitness and wellness budget - 💻 MacBook Pro - 🖥️ $200 home office setup budget - 🎓 Training and development budget - *We have additional benefits depending on location* ## If this sounds like you, we would love to hear from you 🙌 *At Cryptio, we move fast and take ownership of outcomes. We learn from failures, celebrate wins, and let humility, curiosity, and a passion for crypto guide how we work. If you value collaboration and want to build with purpose, you'll feel right at home here.* When applying, mention the word CANDYSHOP to show you read the job post completely.