Forward Deployed AI Engineer

Pick the right model for each job, from frontier APIs to open-weight models, and know when fine-tuning beats a better prompt.

Fine-tune when it pays off: supervised fine-tuning, preference optimization, and parameter-efficient methods like LoRA.

Build the evaluation harnesses and benchmarks that tell us whether a change made things better.

Take models from training to serving, and tune inference cost, latency, and quality.

Sit with the client's team, find where AI moves their numbers, and say no to work that won't pay back.

Experience matters here. We judge it by what you've shipped and kept running, not by a number of years.

You've fine-tuned or post-trained a model and can explain what worked and what didn't.

You've built evals that changed a decision.

You've shipped LLM features that real users depend on.

You've served a model in production and cared about its cost and latency.

You use AI coding tools every day and judge the result by the system and its output, not the language.

A 30-minute conversation with the team about what you've shipped and what we're building.

A technical deep-dive on one system you owned, from the business problem to production.

A working session on a real client problem with the team.

References, then an offer. We aim to finish in two weeks.

Beware of recruitment fraud. All official correspondence comes from a lunon.ai email address. We will never ask you to share bank account information, cash a check, or purchase equipment as part of the hiring process.