Agent Engineer

Build reliable agent capabilities that turn advances in reasoning, planning, memory, and tool use into useful product experiences. This role spans agent systems, platform engineering, integrations, and full-stack product development.

Responsibilities

• Investigate developments in agent technology and identify valuable product opportunities.
• Translate promising model behaviors into reusable skills and workflows that address user needs.
• Build and improve Python agent infrastructure, including orchestration, context management, structured outputs, retries, and error recovery.
• Design tools and integrations for email, calendars, messaging, browsers, documents, CRMs, and business software.
• Own capabilities across Python agents, Django services, APIs, React interfaces, data models, background jobs, observability, and production operations.
• Create platform abstractions that make capabilities easier to compose, extend, and maintain.
• Improve agent execution latency, cost, reliability, and safety.
• Work with evaluation and quality partners to define expected behavior and turn evaluation results into engineering improvements.
• Analyze production traces and user feedback to identify and resolve underlying issues.
• Guide technical decisions on ambiguous problems and contribute to design reviews.

Requirements

• At least 5 years of experience building production software systems end to end, including deployment and operational iteration.
• Strong Python skills and hands-on experience with Django, APIs, React, and TypeScript.
• Experience building or operating agent systems, including planning, tool calling, structured outputs, context and state management, retries, and orchestration.
• Experience designing integrations with external APIs and business software.
• Ability to turn loosely defined user needs and emerging technologies into practical product features.
• Experience owning complex systems in production, including observability, debugging, and improvements based on production signals.
• Skill in designing reusable platform abstractions and diagnosing issues across prompts, model outputs, application code, databases, and APIs.
• Background in LLMs, prompt engineering, or production model evaluation is useful, as is experience optimizing high-volume systems for latency, cost, and reliability.
• Demonstrated career progression within an organization or experience founding a startup, along with strong engineering fundamentals.

Location

On-site in Palo Alto, California, with hybrid flexibility.