Member of Technical Staff (Software Engineer, Enterprise Agent Evals & Efficiency)

Highlights

• Build realistic enterprise eval environments spanning apps, data, and permissions.
• Own the agent improvement loop from measurement to shipped reliability gains.
• Make enterprise workflows faster and cheaper via routing and context efficiency.

What they offer

• Equity

Ideal candidate

Systems-minded engineer who loves ambiguous, end-to-end ownership and turning messy agent failures into measurable reliability, latency, and cost wins for real enterprise work.

Requirements

• 5+ years of software engineering or ML engineering owning production systems end-to-end
• Strong system design for reliable, scalable experimentation, evaluation, or data-intensive infra
• Strong proficiency in Python, Go, or Rust and ability to work across multi-language stack
• Hands-on experience building, evaluating, or improving LLM apps or agents with tool use
• Deep expertise in evals and grading, agent harnesses and skills, simulations, or model routing and efficiency
• Strong experimental judgment defining success criteria and distinguishing real gains from noise
• Track record leading ambiguous cross-team initiatives and raising engineering quality