Agent Engineer

About the Role

This role sits at the intersection of agent systems, platform engineering, integrations, and product development at an early-stage AI productivity startup. You will define and build the core capabilities of an AI assistant that executives and founders rely on for real, high-stakes work. Your work directly shapes what the product can do and how dependably it does it.

What You'll Do

• Investigate advances in reasoning, planning, memory, tool use, and agent collaboration to identify valuable product opportunities.

• Translate promising model behaviors into reliable, reusable skills and workflows that solve real user problems.

• Build and evolve a custom Python agent harness, including execution loops, orchestration, context management, structured outputs, retries, and error recovery.

• Design agent tools and integrations across email, calendars, messaging platforms, browsers, documents, CRMs, and business software.

• Own capabilities end-to-end across the Python agent, Django services, React interfaces, data models, background jobs, observability, and production operations.

• Build platform abstractions that make capabilities easier to compose, extend, and maintain as the product grows more sophisticated.

• Improve latency, cost, reliability, and safety across high-volume agent execution.

• Partner with the Agent Evaluations team to define expected behavior, instrument capabilities, and turn quality findings into engineering improvements.

• Study production traces and user feedback to understand where users lose trust, then fix the underlying system.

• Set technical direction on ambiguous problems and raise the engineering standard through design reviews and thoughtful execution.

What We're Looking For

• 5 or more years building production software systems end-to-end, including design, implementation, deployment, and operational iteration.

• Strong Python proficiency: maintainable production code, asynchronous systems, and sound abstractions.

• Hands-on experience building agent systems, including planning, tool calling, structured outputs, context management, state management, retries, and orchestration.

• Full-stack capability with deep Python and Django expertise, plus comfort working with APIs, React, and TypeScript.

• Experience designing and building integrations with external APIs and business software platforms such as email, calendars, messaging, and CRMs.

• Experience designing reusable platform abstractions that enable composition, extension, and maintenance at scale.

• Analytical debugging ability across prompts, traces, model outputs, application code, databases, and user interactions.

• Product judgment to turn vague user needs and emerging technical possibilities into simple, useful capabilities without requiring complete specifications.

• Strong CS fundamentals, ideally from an engineering-focused academic background.

• Prior startup experience or demonstrated career progression with increasing ownership within a single organization.

• Familiarity with LLM-based systems, prompt engineering, or model evaluation in production is a plus.

• Experience with agent frameworks such as LangChain or AutoGen is a plus.

• Background in workflow automation, autonomous systems, or distributed systems optimization is a plus.

Location

On-site in Palo Alto, CA with hybrid flexibility. Visa sponsorship is not available for this role.