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Staff Software Engineer, AI Data Platform

Staff-level engineer building AI data platform infrastructure, eval systems, and agent-first tooling for frontier labs. Requires 4+ years shipping production systems, full-stack experience, and deep TypeScript/Python proficiency.

250k – 280kSan Francisco, CAML EngineeringHybrid4+ YOE

About the role

What you may work on

  • Eval systems that run millions of agent trajectories to measure model and product quality.
  • Fine-tuning pipelines that turn evaluation signals into measurable agent improvements.
  • Agent-first product surfaces: UX and infrastructure for workflows where the user is a model or an agent operator.
  • The systems behind hundreds of thousands of AI interviews used to source and match freelance workers to projects.
  • Infrastructure that scales to the throughput frontier labs actually need.
  • Integration of the latest models and capabilities into production within days of release.

What we're looking for

  • 4+ year track record of shipping systems customers and other engineers rely on
  • You build full stack prototypes fast and they hold up. The v1 you ship becomes the foundation the rest of the team builds on.
  • Strong system and API design judgement
  • Hard architecture and product calls land with you. You make them, defend them under pressure, and update fast when someone else is right.
  • You ship production code with coding agents daily. You know where they break and what it takes to make them reliable to further accelerate the team's velocity.
  • You set direction by being the example. Other engineers reach for your designs and your code as the reference.
  • You move fast in ambiguous, startup-pace environments with influence over authority.
  • You have worked in all parts of the stack
  • Deep proficiency in TypeScript and/or Python.

Nice to have

  • Production experience building LLM- or agent-driven products.
  • Designing evaluations for LLMs and agents, or producing high-quality data for ML systems.
  • Background in production distributed systems, ML infrastructure, or data systems at scale.

Our Technology Stack

  • Frontend: React.js with Redux, TypeScript
  • Backend: Node.js, TypeScript, Python, some Java & Kotlin
  • APIs: GraphQL
  • Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes
  • Databases: MySQL, Spanner, PostgreSQL
  • Queueing / Streaming: Kafka, PubSub

Skills

TypeScriptPythonReactNode.jsGraphQLGCPKubernetesMySQLPostgresKafka

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