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.