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Khushi Saxena
Junior Full-Stack Engineer specializing in AI systems and distributed backend development
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About
Early-career engineer who built and launched a zero-to-one AI-driven approval workflow at SDSU that is used daily by roughly 2,000 university users. They owned the system end-to-end—from FastAPI/PostgreSQL backend to React UI—and showed strong judgment around LLM reliability, using a two-step pipeline, validation checks, and human-review fallbacks to cut manual processing time by about 80%.
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Key Strengths
- Shipped a production AI approval workflow used daily by ~2,000 university users
- Strong end-to-end ownership across database, backend services, and React frontend
- Designed reliable two-step LLM pipeline to reduce hallucinations
- Built human-review fallback to prevent silent routing failures
- Improved operations efficiency with ~80% reduction in manual processing time
- Integrated 10+ inconsistent downstream university systems/APIs
- Pragmatic reliability-focused architecture decisions
- Zero-to-one product execution with minimal oversight
- User-centered scoping through direct interviews with operational staff
- Iterative post-launch improvement using logs, feedback, and added training data
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