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.