Quick overview
Job description
About the Role
Build reliable, production-ready agent capabilities that help users delegate complex work with confidence. This role combines agent systems engineering, platform development, integrations, and full-stack product work.
What You'll Do
Evaluate advances in reasoning, planning, memory, tool use, and agent collaboration to identify useful product opportunities.
Turn promising model behaviors into reusable skills and workflows that solve user problems.
Build and improve Python agent infrastructure, including execution loops, orchestration, context management, structured outputs, retries, and recovery.
Design tools and integrations for email, calendars, messaging, browsers, documents, CRMs, and business software.
Own capabilities end to end across Python and Django services, APIs, React interfaces, data models, background jobs, observability, and operations.
Develop reusable platform abstractions and improve execution latency, cost, reliability, and safety.
Use evaluations, production traces, and user feedback to diagnose issues and improve agent behavior.
Set technical direction for ambiguous problems and contribute to design reviews and engineering quality.
What We're Looking For
At least 5 years of experience building, deploying, and operating production software systems end to end.
Strong Python skills, including maintainable production code and experience debugging asynchronous systems.
Hands-on experience building production agent systems, with knowledge of planning, tool calling, structured outputs, context and state management, retries, and orchestration.
Full-stack experience with Django, APIs, React, and TypeScript.
Experience building integrations with external APIs and business software platforms.
Ability to turn evolving technical capabilities and loosely defined user needs into practical product features.
Experience designing reusable platform abstractions and analyzing production traces across models, application code, databases, and APIs.
Background working with large language models, prompt engineering, or model evaluation in production; experience optimizing distributed systems for latency, cost, and reliability is helpful.
Strong computer science and engineering fundamentals, clear communication, and a track record of ownership and career progression or startup experience.
Location
On-site in Palo Alto, California, with hybrid flexibility. Visa sponsorship is not available.