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Research · Full-time

Applied AI Engineer

Remote · US / CA / EU / UK

Close the gap between what LLMs can do and what a retail investor actually receives, production-grade AI systems that turn raw financial data into clear, trustworthy research.

Kolo delivers institutional-quality equity research to retail investors, no jargon, no noise, no length. As an Applied AI Engineer, you'll build and own the agentic systems that make that possible: prompt pipelines, retrieval layers, eval harnesses, and the orchestration that ties them together.

This is a shipping role, not a research role. You'll iterate on real output that goes to real members on a weekly cadence. The feedback loop is fast and direct: did the brief get better? You'll know by Friday.

You'll work closely with the technical founders and ML team. We want engineers who think about failure modes, care about eval quality, and push back when a prompt change silently degrades output.

You probably

4+ years of software engineering with meaningful AI/LLM work in production
Deep Python proficiency, agentic systems, structured outputs, orchestration
Experience with RAG pipelines, vector search, and retrieval-augmented generation
Hands-on with LLM APIs: Claude, OpenAI, or similar, not just wrapper libraries
Have built and run eval frameworks; you don't trust vibes to measure prompt quality
Previously worked at an early-stage startup
Remote work experience

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