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Henry Wu
Mid-level Software Engineer specializing in backend, cloud infrastructure, and AI systems
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About
Built and launched a production self-healing MLOps agent that autonomously diagnosed and fixed model training failures on Kubernetes GPU infrastructure. Combines deep AI infrastructure knowledge with full-stack product ownership, and has delivered measurable impact including 35% less infrastructure waste, nearly 50% less troubleshooting time, and 60% lower LLM API costs.
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Key Strengths
- Shipped production AI agents used on expensive GPU workloads
- Deep MLOps and AI infrastructure expertise
- Designed safe autonomous systems with guardrails and structured tool execution
- Strong full-stack ownership across React UI and FastAPI backend
- Built resilient long-running agent workflows with crash recovery via Redis
- Improved infrastructure efficiency with pre-flight validation reducing waste 35%
- Cut engineering troubleshooting time by nearly half
- Optimized LLM cost and latency with hybrid routing and context pruning
- Reduced API token costs by 60%
- Reduced agent response time from 15 seconds to under 4 seconds
- Maintained 95% diagnostic accuracy with condensed context pipelines
- Zero-to-one execution from concept to production launch in 8 weeks
- Effective cross-functional alignment using transparent reasoning trace UX
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Experience
Education
Awards
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Publications
2 publications
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