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Abhiroopsudansh Karengula
Mid-level AI/ML Engineer specializing in production ML, RAG systems, and MLOps
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About
AI/ML Engineer at Black & Veatch who built and productionized an internal RAG-based engineering search platform end-to-end (LangChain/FastAPI/FAISS/Hugging Face on AWS Kubernetes), adopted by 400+ engineers and credited with a 42% reduction in technical lookup time/support escalations. Also modernized a legacy batch equipment-failure ML pipeline into a real-time Kafka/Spark system using shadow deployments, drift checks, and MLflow-based rollbacks.
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Key Strengths
- Owned and shipped end-to-end production RAG search platform (frontend/backend/data/infra)
- Production-grade LLM/RAG testing strategy (unit, API-level, offline eval sets with real queries)
- Built guardrails and monitoring for LLM systems (source grounding, fallbacks, sensitive-query handling, quality dashboards)
- Scaled deployment on AWS Kubernetes with autoscaling and reliability focus
- Delivered measurable impact: 400+ engineers adopted; 42% reduction in lookup time/support escalations
- Legacy modernization from batch ML to real-time streaming with Kafka/Spark and shadow deployment validation
- Risk-managed rollout with side-by-side metrics, drift detection, gradual traffic shifting, and rollback via MLflow
- Effective context switching across multiple initiatives with 1–2 week milestone delivery
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