AI Engineer (Full-Stack)

Responsibilities

• check_circle Own one or two product surfaces end to end: the UI, the Postgres schema underneath, the edge functions in between, the deploy, and what happens after it.
• check_circle Build and operate the LLM-backed parts of the product: prompts, retrieval, evals, cost and latency, and validating output you cannot fully trust.
• check_circle Turn a customer objection or a call transcript into shipped product, making the judgement calls in the middle yourself.
• check_circle Build with agents as your normal working method, and take responsibility for what they produce.
• check_circle Make the codebase easier for the next person and the next agent: sharper rules, better skills, gates that catch problems before a human reads the PR.
• check_circle Talk to the people using this. Our customers are recruiters who will tell you exactly what is broken.
• check_circle Small team, fast decisions. You will be in the room where they get made.
• check_circle Linear tracks reality, moved as work happens, not batched at the end.
• check_circle Feature branches, PR review, squash merge. main is protected and deploys on merge.
• check_circle Agents draft, humans approve, the system logs it.
• check_circle Async by default, with regular time together in person.

Basic qualifications

• You have shipped full-stack features and operated them: migrations, auth, deploys, and the 2am production debugging.
• You have shipped something with an LLM in the critical path and kept it working. You know what breaks, what it costs, and how you tell whether it is getting better.
• You have worked inside a real engineering pipeline, in a team that had standards: branches, review, CI, releases. You know what good looks like and you will not need it invented around you.
• You build with coding agents every day, and you can explain how you prompt, review, and validate what comes back. You delegate the volume and keep the judgement on architecture, data, and security.
• You can read and reason about code you did not write. When an agent produces something plausible and wrong, you catch it.
• You notice when something is off and you fix it, rather than filing it.
• You do not need to be told what is next. And when something is genuinely missing, a key, a decision, an account, you ask immediately instead of quietly working around it.
• You want more responsibility than you have been given so far. That is the actual offer here.
• Security: auth, tenant isolation, secrets, dependency hygiene, GDPR.
• Supabase in production, especially RLS and edge functions.
• Real Postgres depth.
• js, Node, or Python.
• Multi-tenant B2B SaaS. Recruitment or HR tech.
• You have built your own agents, skills, or tooling.
• A 30-minute call.
• A technical conversation where you walk us through something you built and we read code together.
• A case. A real problem from our world: a customer objection and a slice of the product. How would you approach it, what would you build first, and what would you refuse to build. We discuss it together, we are not marking an exam.
• A conversation with our CEO and our product lead, references, and an offer.

Benefits