Gen AI LLMOps Engineer

Job Description:

• We are looking for a GenAI LLMOps Engineer to operationalize and scale Large Language Models LLMs and Generative AI applications in production environments
• This role focuses on LLM deployment orchestration monitoring and optimization ensuring reliable and efficient GenAI systems

Key Responsibilities:

• LLM Deployment Productionization
• Deploy and manage LLMs OpenAI Llama Mistral etc
• in production environments
• Build scalable inference pipelines real time batch
• Integrate LLMs into applications via APIs and microservices
• LLMOps GenAI Pipeline Development
• Design and implement end to end LLM pipelines
• Prompt engineering
• Retrieval Augmented Generation RAG
• Fine tuning embeddings
• Work with frameworks like
• LangChain LangGraph LlamaIndex
• RAG Data Integration
• Build and optimize RAG pipelines using vector databases
• Work with tools like
• Pinecone FAISS Weaviate Chroma
• Handle document ingestion chunking indexing and retrieval
• Model Monitoring Optimization
• Monitor LLM performance
• Latency
• Accuracy hallucinations
• Cost efficiency
• Implement
• Prompt optimization
• Feedback loops
• Guardrails evaluation frameworks
• MLOps for LLMs
• Build CI CD pipelines for
• Model updates
• Prompt version control
• Manage experiment tracking and deployments
• Ensure reproducibility of LLM workflows

Technical 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

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 pipelines
• Operationalizing GenAI applications

Preferred Skills:

Technology->AI-Generative AI->Generative AI for Data Analytics