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TejaSree Chiluveru
Mid-level Software Engineer specializing in FinTech and cloud-native microservices
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About
Built and launched an internal AI troubleshooting assistant focused on safe, retrieval-first root cause analysis for enterprise systems, with strong attention to monitoring, fallback behavior, and post-launch iteration. Also owns full-stack product work across React and Java/Spring Boot, including high-volume financial operations workflows, and reports measurable LLM improvements such as ~30-40% latency reduction.
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Key Strengths
- Production AI agent development with safety-focused architecture
- Strong RAG system design and retrieval optimization
- Reliability and observability for AI and backend systems
- End-to-end ownership across React UI and Java/Spring backend
- Performance optimization for high-volume data workflows
- Practical LLM evaluation using user feedback and test sets
- Iterative product improvement driven by post-launch signals
- Zero-to-one scoping under ambiguity
- Cross-functional collaboration with product and design
- Latency reduction of ~30-40% in LLM-powered workflow
- Safe tool design with read-only production constraints
- Idempotency and duplicate-processing prevention in APIs
Reference Highlights
- leadership
- mentorship
- growth mindset
- positive attitude
- supportive
- reliable
- calm under pressure
- composed during incidents
- effective incident resolution
- clear communication
- strong end-to-end understanding
- quick problem-solving
- cross-functional collaboration
- customer-focused execution
- incorporates feedback well
- iterates quickly
- strong ownership
- handles ambiguity well
- breaks down loosely defined problems
- identifies sensible starting points
- maintains focus
- drives execution
- balances speed with quality
- practical tradeoffs
TejaSree's references speak for themselves. Let us connect you.
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