An engineer who
builds platforms + automates infrastructure
+ writes production-grade systems

Architected an end-to-end AI observability platform leveraging Claude Sonnet 4.5 LLM for intelligent anomaly detection, automated root cause analysis, and real-time Kubernetes log streaming across enterprise-scale deployments.

• Architected end-to-end AI observability platform using Java 21, Spring AI & Claude Sonnet 4.5 LLM — achieving 95% anomaly detection accuracy with 2-3 second analysis latency
• Engineered real-time Kubernetes log streaming & event aggregation, reducing MTTR by 60–80% through automated root cause analysis
• Built scalable microservices supporting 100+ pods with minimal resource usage & 99.9% system reliability via heuristic fallback mechanisms
• Delivered $850K annual cost savings and projected 650%+ ROI in first year through reduced incident response time
• Led proof-of-concept from inception to completion in 4 weeks — comprehensive docs, perf benchmarking & integration testing
• Established Helm charts + Docker containers deployment strategy for seamless production rollout across multiple environments

The Insurance Billing System (IBS) — processing and tracking all policy receivables, payables, billing, and payment information.

• Developed and maintained key modules: Refund, Disbursement, Policy Locks & Doc Director
• Implemented and optimised batch jobs for various modules, ensuring performance and reliability
• Collaborated with stakeholders to understand workflow and assess business impact of system changes