🚀 Data Infrastructure Engineer – AI / Financial Data
đź“Ť Hybrid
đź’° 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 đź§
• 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
Tech ⚙️
• Python
• Async systems / queues / web scraping
• Postgres / SQLite
• AI agents & LLM workflows
• Data pipelines & infrastructure
Why it’s interesting 💡
• 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