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Omkar Bhambure
Mid-level Software Developer specializing in backend microservices for healthcare and FinTech
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Built and deployed an AI-powered insurance claims fraud platform end-to-end using Java/Spring Boot, Kafka, OpenAI, pgvector, and AWS EKS. Stands out for combining LLM/RAG architecture with production-grade scalability and observability, delivering measurable impact including 62% less manual review, 40% better fraud precision, 37% higher throughput, and 99.95% uptime.
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Key Strengths
- End-to-end AI platform deployment ownership from discovery through post-launch stabilization
- LLM/RAG production architecture for insurance claims fraud detection
- Scaled Kubernetes workloads to 10K+ concurrent events with 99.95% production uptime
- Reduced manual review workload by 62%
- Improved fraud detection precision by 40%
- Performance optimization via Redis caching and asynchronous multithreaded inference
- Increased system throughput by 37%
- Built observability across 25 microservices with Prometheus and Grafana
- Strong incident mitigation using human fallback routing and temporary static filters
- Stakeholder management through quantifiable milestones and trust-building during AI rollout
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