About the role
Requirements:
- 4+ years of software engineering experience with strong Python proficiency and at least 2 years of hands-on work building AI/ML-powered production systems.
- Deep, practical experience with LLM APIs in production prompt engineering, output parsing, structured extraction, token management, error handling, and retry strategies.
- Experience building document understanding or information extraction pipelines: OCR, PDF processing, form extraction, or NLP-based data extraction at scale.
- Strong understanding of evaluation methodology; you know how to measure extraction quality, build ground truth datasets, and set up automated regression testing for AI outputs.
- Hands-on experience with at least one LLM observability or evaluation platform (Langfuse, LangSmith, Braintrust, Weights and Biases, or equivalent).
- Production experience with AWS or equivalent cloud platform where you've deployed and monitored AI pipelines, not just run notebooks.
- Daily, habitual use of AI tools in your own engineering workflow Claude Code, Copilot, Cursor, or equivalent for coding, debugging, and research.
- Ownership mindset: you don't wait for someone to hand you a perfectly scoped ticket; you identify extraction quality issues, propose solutions, build them, and measure the impact.
- Clear communication skills you can explain model tradeoffs, extraction accuracy metrics, and pipeline architecture to product managers and engineers who aren't AI specialists.