- AI Engineering: Agent systems, multimodal pipelines, applied LLM workflows
- System Building: From prototype → production, focus on scalability & reliability
- Problem Framing: Turning vague demand into executable architectures
I care less about models, more about systems that survive reality.
AI / ML
- LLM Applications · Agentic Workflows · Multimodal Systems
- RAG · Tool Calling · Evaluation & Feedback Loops
Engineering
- Python-centric systems
- Modular design · Config-driven architecture
- Containerized & reproducible workflows
Build systems, not demos.
Optimize for leverage, not noise.