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vamshi saggurthi
Mid-Level Software Engineer specializing in LLM agents and real-time data streaming
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About
Software engineer with experience at Striim and Amazon who ships end-to-end production systems across UI, backend, ML, and operations. Built a real-time PII detection capability for a streaming data platform by integrating Python ML inference into a Java monolith via gRPC sidecars, achieving ~3M events/hour throughput and ~93% accuracy, and helped drive enterprise adoption (Fiserv, CVS). Also modernized internal Amazon tooling for multi-region scale with modularization and fully automated deployments.
Experience
Education
Key Strengths
- Owned end-to-end real-time PII detection feature (UI, ML model, gRPC integration, containerization, deployment, docs)
- High-throughput, cost-efficient ML inference at scale (~3M events/hour; ~93% accuracy; ~23 PII fields)
- Strong cross-language architecture decisions (Java monolith + Python sidecar via gRPC; batching/streaming/connection reuse)
- Production-grade AWS operations (CloudFormation/CDK, Lambda/S3/Step Functions, multi-env accounts, canary/phased rollouts, CloudWatch + Prometheus/Grafana)
- Improved maintainability by decomposing a fragile monolith into modular packages and automating deployments (region expansion from ~5 to 25; deploy time from ~1 week to ~5 minutes)
- Built resilient ingestion/embedding pipelines with Kafka, retries, DLQs, alerting, and backfills across flaky third-party APIs
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