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Janvitha Mandyam
Mid-level GenAI/ML Engineer specializing in LLM applications and RAG systems
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About
GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.
Experience
Key Strengths
- Built and deployed production RAG system for global bank (LangChain + FAISS/Azure Cognitive Search + GPT-4/Claude)
- Hallucination mitigation with RAG-first grounding, Guardrails validation, confidence thresholds, and safe fallbacks
- Measurable impact: improved Q&A accuracy by 35% and reduced handle time/escalations
- Designed LLM evaluation framework using golden sets, adversarial cases, and groundedness/citation metrics (TruLens/PromptLayer)
- Production-grade deployment: containerized microservices on Kubernetes with FastAPI + React and streaming responses
- Latency and cost optimization via dynamic context windows and tiered model routing
- Orchestrated multi-agent/tool workflows (LangChain/LangGraph) and automated ML pipelines (Kubeflow/Vertex AI)
- Cross-functional delivery with non-technical stakeholders via workshops and iterative dashboard/NLG solutions (CVS Health)
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