Competitive Salary + Equity
We’re working with an early-stage AI company building infrastructure that transforms large volumes of unstructured financial data into clean, queryable datasets used by major financial institutions.
They’re looking for a Data Infrastructure Engineer to own data pipelines end-to-end — from ingestion and transformation through to delivery — while working closely with AI agents and LLM-powered workflows.
What you’ll be doing
- Building and scaling production‑grade data pipelines handling large volumes of messy, unstructured data
- Designing ingestion, transformation, storage, and delivery systems end‑to‑end
- Working with AI agents and LLM workflows for document extraction and data processing
- Improving reliability, observability, and data quality across the platform
- Helping shape the architecture of an AI‑native data platform from an early stage
What they’re looking for
- Experience building and owning production data pipelines
- Strong Python engineering skills
- Experience working with unstructured data at scale
- Exposure to AI agents, LLMs, or orchestration workflows in production
- Background in fintech, market data, or similar high‑trust environments is a plus
- Engineers who care deeply about data quality and correctness
- AI agents & LLM workflows
- High ownership from day one
- Strong mix of AI infrastructure + data engineering
- Real‑world financial datasets with meaningful complexity
- Small, highly technical team with strong traction
- Opportunity to grow into a broader platform / technical leadership role
