Gen AI LLMOps Engineer (Karnataka)

Educational Requirements Bachelor of Engineering,BTech,BCA,BSc,MCA,MTech,MSc Service Line Data Analytics Unit Responsibilities - LLM Deployment ProductionizationDeploy and manage LLMs (OpenAI, Llama, Mistral, etc.) in production environmentsBuild scalable inference pipelines (real-time batch)Integrate LLMs into applications via APIs and microservicesLLMOps / GenAI Pipeline DevelopmentDesign and implement end-to-end LLM pipelines:Prompt engineeringRetrieval-Augmented Generation (RAG)Fine-tuning / embeddingsWork with frameworks like:LangChain, LangGraph, LlamaIndexRAG Data IntegrationBuild and optimize RAG pipelines using vector databasesWork with tools like:Pinecone, FAISS, Weaviate, ChromaHandle document ingestion, chunking, indexing, and retrievalModel Monitoring OptimizationMonitor LLM performance:LatencyAccuracy / hallucinationsCost efficiencyImplement:Prompt optimizationFeedback loopsGuardrails evaluation frameworksMLOps for LLMsBuild CI/CD pipelines for:Model updatesPrompt/version controlManage experiment tracking and deploymentsEnsure reproducibility of LLM workflows Additional Responsibilities: - What This Role Is NOT Not pure:Data Scientist (model building only)Platform Engineer (infra-heavy role)Traditional MLOps without LLM exposure This role focuses on:LLM deployment + RAG + GenAI pipelinesOperationalizing GenAI applications Technical and Skilled Requirements: - Strong Python programming - Hands-on experience with LLMs / Generative AI - Experience with:LangChain / LangGraph / LlamaIndex - Solid understanding of:RAG architecture - Prompt engineering - Embeddings vector search - Experience building APIs using:FastAPI / Flask Preferred Skills: - Technology->AI-Generative AI->Generative AI for Data Analytics .