About the role
This is a founding-level engineering role where you will own the entire AI and backend stack end-to-end, from architecture to production. You won't just build features; you'll define how AI powers lending decisions at scale.
Your responsibilities will be across the following functions:
AI-Native Systems:
- LLM-powered document intelligence pipelines for financial data extraction and analysis.
- Internal deal intelligence and credit decisioning platforms.
- Agentic workflows for document processing, report generation, and workflow automation.
Backend and Platform:
- Scalable backend APIs and system architecture for lending workflows.
- RAG pipelines over financial documents, borrower data, and internal knowledge.
- Prompt engineering and evaluation frameworks for consistent AI output quality.
Infrastructure and Reliability:
- Cloud-native systems on AWS/Azure (CI/CD, Docker/K8S, monitoring, and security).
- Full ownership of production systems.
Requirements:
- 4-8 years of backend engineering in Python (FastAPI / Django).
- Hands-on with LLM stack: LangChain / LlamaIndex, RAG, vector DBs, prompt engineering.
- Strong experience with cloud-native systems (AWS/Azure, CI/CD, containerisation).
- Have shipped at least one production-grade AI/RAG system (not just POCs).
Good-to-haves:
- Supabase / Vercel / Railway stack.
- Experience in financial documents/lending/fintech workflows.
- Full-stack exposure (React / Next.js ).
- Early-stage startup or founding engineer experience.