- Design and delivery of production AI and agentic systems across document intelligence, workflow automation, and copilots
- Architecture decisions for LLM-based systems, including retrieval, tool use, orchestration, memory, and evaluation
- Evals and observability for production AI to ensure system performance and reliability
- Cost and latency management at production volume
- Partnership with AI product on scoping and sequencing features
- Partnership with data engineering on the pipelines, schemas, and data quality
- Technical mentorship of other engineers working on AI-adjacent systems
- Vendor and model evaluation, including POCs, benchmarks, and cost-performance tradeoffs
AWSPythonPrompt Engineering