The operating system for agentic AI in high-consequence environments. Backed by Costanoa Ventures.
About the role
Nebula, our agentic harness, turns days of manual synthesis into minutes of analysis for analysts across the Intelligence Community and the Department of Defense. Whether that is true on a given day comes down to the intelligence layer: how agents reason, retrieve, call tools, and produce output an analyst can trust. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 2+ years of professional software engineering experience shipping production code, with strong Python. Candidates with 4+ years will be considered at the senior level
- Experience shipping at least one LLM-powered feature to real users, and knowing how you knew it worked: the eval, the metric, and what you changed because of it
- Hands-on experience with at least one of retrieval pipelines, tool use and function calling, or agent orchestration
- Experience designing evaluations for non-deterministic output and iterating on prompts, retrieval, and tooling based on what fails
- Strong software fundamentals: testing, code review, typed interfaces, and code that survives constant change
- Comfort taking a loose ask and turning it into a working feature without a fully specified ticket
More about this role
Lumbra builds the vendor-neutral operating system for agentic AI in high-consequence environments. In our first ten months we won four fully competed prime contracts across the U.S. Government, every one of them deploying into classified spaces. We are live on JWICS. We were selected from a field of 200+ companies for a defense innovation challenge and won it. We beat two established defense primes on the same program and earned the follow-on, now in execution.
Nebula, our agentic harness, turns days of manual synthesis into minutes of analysis for analysts across the Intelligence Community and the Department of Defense. Whether that is true on a given day comes down to the intelligence layer: how agents reason, retrieve, call tools, and produce output an analyst can trust.
We want an Applied AI Engineer to turn models into product features that analysts actually use. You build agents, retrieval, and tool integrations into Nebula, you prove they work with evaluation rather than demos, and you ship them as production code.
This role is on site in New York City. It is not eligible for remote or hybrid work.
~60% building. Agent behaviors, retrieval pipelines, tool integrations, and...
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