FP&A software that gives finance a strategic advantage with on-demand data, deeper insights, automated reports, and seamless spreadsheet integrations. Backed by Y Combinator.
About the role
Own the AI foundation product teams build on: model selection and routing, the model proxy layer, context management, and tool design Own eval infrastructure. Work with customers and finance domain experts to define what excellent output looks like, then encode it in evals every team can run - in FP&A, a wrong answer ends up in someone's board deck
What they're looking for
- You've shipped production LLM systems - evals, context management, multi-model or multi-provider routing - and can talk concretely about what broke and what you changed
- You build proof of concepts, decide quickly, and ship v0s. Evals drive your quality bar
- Strong judgment about abstractions: opinionated about design, pragmatic about shipping incrementally
- Experience with LLM APIs and agent frameworks, and shipped user-facing products
- You want to ship production systems, not do research
More about this role
Aleph is an AI-native platform for Financial Planning & Analysis (FP&A), an established software category with a multi-billion market but no clear winner. We’re trying to solve a problem many finance teams are super familiar with: data scattered across a million systems, endless spreadsheets and way too much time spent getting numbers to line up instead of actually using them to make decisions.
Aleph was founded by Albert Gozzi and Santiago Perez De Rosso, two technical founders with backgrounds from Stanford and MIT and experience working at top-tier companies such as Google, Microsoft and Bain & Company. We’re backed by top VCs (Khosla Ventures, Bain Capital Ventures, YC, Picus Capital), and work with customers like Webflow, Notion, Zapier, Y Combinator and many others.
We are hiring remotely across the Americas (United States, Canada, LATAM).
Every AI feature at Aleph - asking questions of your financials, agents that do full FP&A workflows - runs on a shared foundation: which model handles which task, what context the model sees, what tools it can call, and how we measure whether it's getting better. Today those decisions live inside product teams. This role owns them as a...
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