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.

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.