- Own end-to-end delivery of AI product features
Lead the design and implementation of complex features—from initial concept through production—ensuring high quality and strong user impact.
- Drive system design for AI-backed experiences
Architect systems that orchestrate LLMs, retrieval, and structured data, making thoughtful tradeoffs between flexibility, reliability, and performance.
- Elevate product quality through iteration and evaluation
Establish and improve feedback loops (evaluation frameworks, user signals, experimentation) to systematically improve AI output quality.
- Lead technical direction within a product area
Break down ambiguous problems, define approaches, and guide execution across multiple engineers.
- Mentor and raise the engineering bar
Provide guidance on code quality, system design, and product thinking; help less experienced engineers operate more effectively in an AI-driven environment.
- Accelerate team velocity through AI-assisted development
Model effective use of modern AI tools to improve iteration speed, code quality, and overall team productivity.