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Alex ZhuZhou
Intern Full-Stack Software Engineer specializing in AI/LLM platforms and data systems
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About
Backend/LLM engineer with experience productionizing RAG systems (legal-case natural language querying) and optimizing for latency/cost, including a reported ~40% reduction via Redis caching and batching. Built monitoring and real-time debugging workflows (FastAPI, structured logging, correlation IDs, sandbox repro) and regularly delivered technical demos/workshops. Also partners with BD/sales to translate LLM capabilities into business value, including ESG-metric extraction from corporate filings.
Experience
Education
Key Strengths
- Took an LLM RAG prototype to production by benchmarking embeddings/vector DBs and implementing cloud autoscaling
- Reduced latency and LLM API costs ~40% via Redis caching and batching changes
- Maintained output quality with automated regression tests using semantic similarity thresholds plus confidence scoring for cache refresh
- Strong real-time troubleshooting: structured logging/metrics, correlation IDs, sandbox reproduction for deterministic debugging
- Effective technical communication: tailored demos/workshops for developers vs non-technical stakeholders; uses live coding and feedback loops
- Bridges technical and business value in customer-facing meetings; created client-facing technical collateral to drive adoption
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