About the job
Kepler: The AI you can trust and verify.
Every AI tool has inherent flaws: the model interacts with data, leading to inaccuracies—be it fabricating sources or providing inconsistent answers. For those making crucial million-dollar decisions, this isn’t just a flaw; it's a dealbreaker.
At Kepler, we have engineered an architecture that makes hallucination structurally impossible. Our AI interprets your intent while deterministic code retrieves precise figures from source documents. The model never generates arbitrary numbers, ensuring every output can be traced back to a filing, a page, or a line item, with every calculation clearly showing its formula. This guarantees defensibility in all answers.
In production, we handle over 950K SEC filings, 14K+ companies, and 40M+ documents across 27 global markets, trusted by firms that can't afford to be wrong.
Our architecture is domain-independent, starting with finance where the pain points are most acute, and extending to healthcare, legal, and insurance sectors. We’re not just creating a finance product; we're building the verification layer for the entire AI ecosystem.
Founded by Vinoo Ganesh (7 years at Palantir, former Head of Business Engineering at Citadel) and Dr. John McRaven (11 years at Palantir, creator of the analytics engine behind $100M+ contracts with BP and Airbus, Ph. D. in Physics). We are backed by the founders of OpenAI, Facebook AI Research, MotherDuck, dbt, and Outerbounds.
The Role
As the Head of AI Research, you will set the research agenda to ensure AI is trustworthy for enterprise decision-making. At Kepler, we’ve tackled hallucination not by enhancing model intelligence but by designing systems where such issues cannot occur. AI interprets intent, and code retrieves data, linked through a semantic layer. Every output is directly traced to its source.
We are seeking an innovative leader to advance the boundaries of what is achievable within this architecture.
You will spearhead research in agentic systems, memory architectures, retrieval techniques, and evaluation frameworks. You will have access to unique financial data, including structured filings, earnings transcripts, market feeds, research reports, and live audio—all normalized with full provenance. This isn't another lab creating demos; your contributions will directly impact production, empowering financial professionals who make high-stakes decisions.
This position is perfect for researchers eager to develop AI systems that operate effectively in high-stakes environments, where every answer is substantiated and every insight can be traced back to the truth.

