Supabase Software Engineer on the AI Tooling team responsible for building and operating backend services behind Supabase’s AI products. This role focuses on service reliability, authorization, observability, and scaling in a fast-paced environment.
Responsibilities
We’re looking for a Software Engineer, AI Tooling Infrastructure to join our AI Tooling team and help build and run the backend services behind Supabase’s AI products. The Supabase MCP server is one example of what the team runs in production, alongside the services that support agent skills and the dashboard assistant. You’ll work closely with the Platform, SRE, Auth, Billing and Edge Functions teams, and with the engineers on the AI Tooling team who build the product surfaces.
The AI Tooling team runs its own services in production and carries its own on-call. Traffic from AI clients and agents behaves differently from traffic from people: hundreds of calls a minute, retry loops, and no reading of deprecation warnings. This role makes sure the services they use are reliable, correctly authorized and observable. It is a systems and infrastructure role rather than a product AI role, and it is not an SRE role. You will build and operate these systems, not only advise on them.
This role is ideal for someone who thrives in async, fast-paced environments, owns what they ship in production, and is excited about building developer tools that scale to millions.
What You’ll Be Responsible For
Build and operate the production backend services behind Supabase’s AI products, including the MCP server: deployment, scaling, configuration and release.
Take ownership of how those services are structured, including splitting or reshaping a service when that makes it safer to run and easier to change.
Define, measure and meet reliability targets for the services the team runs. Set SLOs with the SRE team, track error budgets, and use them to decide what to fix first.
Participate in the AI Tooling team on-call rotation, and be a first responder for incidents in those services. Investigate, fix, coordinate with other teams during incidents, and write the follow-ups and runbooks.
Work the AI Tooling team support queue alongside on-call, and turn recurring issues into fixes rather than repeated manual answers.
Own authentication and authorization for AI and agent clients: OAuth apps, scoped tokens, and permissions that make sense for agents as well as humans, including how we change or deprecate a permission without breaking existing integrations.
Own observability for the services the team runs: metrics, traces, logs, dashboards and alerts, so we find problems before customers do.
Handle capacity and abuse for agent traffic: rate limits, cost and safety controls, and behavior under load or when a dependency degrades.
Qualification
Write strong TypeScript or GoKnow OAuthAre comfortable with CI/CDCan debug across servicesCommunicate clearly in writingPick your centre of gravityAPIs and authOperationsExperience with GrafanaOpen-source contributions
Required
Have 5+ years of experience building and running backend services in production, and have carried on-call for them.
Write strong TypeScript or Go, and are comfortable working in the other.
Have designed and operated APIs with real consumers: versioning, error handling, rate limiting, and backwards-compatible change.
Know OAuth, OIDC, JWT and API authorization well enough to debug them in production and to explain where implementations commonly deviate from the spec.
Have a good understanding of PostgreSQL and relational databases.
Are comfortable with CI/CD, Docker and containerized deployments, and with infrastructure as code. Any tool is fine.
Can debug across services: follow a slow or failing request through several systems using metrics, traces and logs.
Communicate clearly in writing, work with a wide range of stakeholders, and thrive in async, globally distributed teams.
Are comfortable navigating ambiguity and moving quickly.
Pick your centre of gravity. We expect you to be deep in at least one of these, and to tell us which:
APIs and auth: You have designed permission models, token scopes or OAuth flows for third-party or machine clients, and you have migrated them without breaking users.
Operations: You have run production services yourself: carried the pager, written alerts and runbooks, used SLOs or similar to decide what to fix, and made shared systems less risky over time.
Preferred
Experience with agent tooling (MCP or similar), or serving traffic from AI agents and LLM clients.
Experience moving a service out of a larger codebase while keeping existing clients working.
Experience with Grafana, OpenTelemetry, Logflare or a similar observability stack, and real SLO work.
Open-source contributions, especially to Node.js, Go, TypeScript or API tooling.
