Harness Engineer

Nomic AI

Harness Engineer developing systems for AI agents at Nomic to extract information from complex document sets. Working on retrieval systems and evaluation for agent performance at scale.

Posted 6/2/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonTypeScript

About the role

Key responsibilities & impact

Work on retrieval systems — search, ranking, chunking strategies, hybrid approaches, knowing which tool fits which problem
Context engineering — assembling the right information for agents operating over large, heterogeneous document sets
Evaluation and harnesses — building the infrastructure to continuously measure agent accuracy, regression-test retrieval quality, and close feedback loops
Agent pipelines — the orchestration layer between retrieval, models, and downstream actions
Scale — making all of the above work across thousands of customer document collections, not just a demo corpus

Requirements

What you’ll need

Strong software engineering skills in Python and/or TypeScript
Real experience with retrieval systems — embeddings, vector search, traditional IR, or some combination
You've built systems that had to work on messy, real-world data — not just clean benchmarks
Familiarity with LLMs and agent frameworks in practice, not just in theory
You think in systems — how components interact, where things break, what doesn't scale
Intellectual curiosity about the retrieval and agent tooling landscape as it exists right now
Experience with evaluation infrastructure — evals, benchmarks, regression testing for AI systems
Background in search, NLP, or information retrieval
Exposure to the AEC industry or other document-heavy domains

Benefits

Comp & perks

Health insurance
Flexible work arrangements

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonTypeScriptretrieval systemsembeddingsvector searchinformation retrievalevaluation infrastructureregression testingNLPagent frameworks

Soft Skills

intellectual curiositysystems thinking