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Navyatej Tummala
Junior Software Engineer specializing in backend, cloud, and AI systems
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New grad software engineer who has already built both a full-stack location-based social app and an internal AI on-call copilot using OpenAI and LangChain. Stands out for combining end-to-end product execution with practical LLM engineering, including RAG, fallback design, citations, and production evals, plus shipping a hackathon-winning MVP in 24 hours.
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Key Strengths
- End-to-end full-stack product ownership
- Serverless application development on AWS
- Strong TypeScript and React implementation
- Practical RAG system design for internal knowledge tools
- Production-minded AI safety with human-in-the-loop boundaries
- AI evaluation and monitoring using retrieval quality, citations, latency, and feedback
- Iterative improvement of LLM systems through chunking and reranking
- Fast MVP execution in ambiguous early-stage environments
- Hackathon-winning product delivery under 24-hour constraints
- Built and deployed a production Slack RAG assistant with citations (OnCall Copilot)
- Reliability-focused LLM system design (confidence thresholds, required citations, abstain behavior)
- Strong handling of messy source data (cleaning, chunking heuristics, metadata)
- Performance and stability optimization (top-k/context tuning, offline fallback, Docker, logging, health checks)
- Evaluation-driven development (labeled test sets, success/citation/abstain/latency/cost metrics, regression evals, drift monitoring)
- Pragmatic model/retrieval selection based on accuracy-latency-cost constraints
- Effective collaboration with non-technical stakeholders (rubrics, demos, iterative UX/prompt improvements)
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