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Laharika Kanchanapalli
Mid-level Cloud DevOps Engineer specializing in AWS/Azure infrastructure and Kubernetes
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About
Backend/ML platform engineer in the insurance domain who built and shipped an AI-driven risk scoring/fraud detection service for underwriting. Runs containerized .NET Core and Python inference services on Azure (AKS + GPU nodes) with Terraform/ARM and Azure DevOps CI/CD, and has hands-on experience improving reliability under peak load plus implementing production AI guardrails (drift monitoring, fallbacks, human review, audit logs).
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Key Strengths
- Built and operated production AI inference APIs on AKS with GPU nodes
- Debugged and resolved peak-load latency/timeouts via memory optimization, right-sized pod resources, and Redis caching
- End-to-end ownership of containerization, deployment, CI/CD, autoscaling, monitoring, and performance tuning
- Designed multi-step policy processing workflows with verification gates and automatic escalation to human review on repeated failures
- Strong production engineering practices in Python: clean layering, typing, testing, structured logging, and observability
- Relational data modeling and query optimization using indexing and query rewrites based on query plan analysis
- Implemented AI production guardrails: audit logs, drift monitoring, fallbacks, and human-in-the-loop escalation for anomalous outputs
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