AI Platform Engineer

Job summary

Responsibilities

We are hiring a AI Platform Engineer to build the execution layer for Supabase's internal AI systems.

• Ship the agent platform to production. An event-triggered queue, a headless model-agnostic runtime (choosing the runtime is an open decision you will close), durable state that…
• Own the evaluation layer, and switch on the gate that depends on it. Golden suites with behavioral assertions rather than intuition, judge criteria with a written rubric, safety…
• Build and register the agent portfolio. Reporting, drafting, linting, triage and question-answering agents across the executive, team-lead and individual-contributor layers, plus…
• Enforce governance in code. Risk tiers the pipeline actually enforces, least-privilege credentials per agent, tool-permission gates, a decision audit log, and autonomy classes…
• Design how the system contacts people. A hard interruption budget per person, message bundling instead of a stream of pings, and a structure that gives something useful before it…

What they're looking for

• Have shipped production LLM agent systems that other people depended on. Not demos, not internal showcases. Systems with operational history, real users and at least one incident…
• Design evaluations, not spot checks. You build golden sets, write behavioral assertions, define judge rubrics, set pass thresholds and gate CI on the result.
• Have done deep API work against the systems work actually lives in, and have authored MCP servers. You know the specific failure modes of those APIs, not just that they exist.
• Own infrastructure end to end in Python on GCP, with a cloud warehouse and infrastructure as code. You provision, deploy, monitor and roll back your own systems, and you close…
• Have taste about how software contacts humans. You treat every notification as spending a limited amount of trust.

Tech stack

• PostgreSQL
• Python
• GCP