Software Engineer, Applied AI

We are looking for someone who wants to build real agent systems, understand how they behave in the wild, and use that understanding to make bold product and architecture decisions.

- Build and improve the core systems behind our agents across retrieval, tool use, document understanding, memory, and orchestration

- Design evals and experiments that help us understand agent quality in production

- Turn traces, failures, and user behavior into concrete product and architecture decisions

- Work closely with operations, GTM, and deployed teams to understand real workflows and where agents break down

- Evaluate models, prompts, and system designs across real enterprise tasks

- Own the loop from idea -> implementation -> measurement -> iteration

- Strong engineering fundamentals and the ability to ship production systems

- Experience building or working on LLM-powered products, agent systems, or adjacent applied AI systems

- An empirical mindset - you reach for logs, traces, experiments, and real usage before guessing

- Strong systems taste - you understand that retrieval, prompting, memory, tools, and UX interact

- Strong opinions about what makes agent systems actually work

- Experience designing evals, benchmarks, or feedback loops for LLM systems

- Experience building internal tools, workflow products, or operator-facing systems

- Experience in startups or other high-ownership environments

This is a new field. We care much more about what you have built than whether your background fits a standard template.

- Designing and shipping an agent harness that materially improved performance on a real task

- Building an eval or benchmark that changed what your team decided to build next

- Designing tool interfaces, memory systems, or retrieval systems for an LLM-powered product

- Building a production workflow around language models that users actually depended on

- Running a careful experiment on prompting, model routing, or orchestration and using it to drive a product decision

If you apply, we would love to see one thing you built with LLMs or agents. It does not need to be perfect or flashy. We mostly want to understand how you think, what you owned, what you learned, and what tradeoffs you made.