LLM Operations Engineer

Project Role : LLM Operations Engineer Project Role Description : Utilize cloud-native services and tools for scalable and efficient deployment. Monitor LLM performance, address operational challenges, and ensure compliance and security standards in AI operations. Must have skills : Generative AI, Large Language Models (LLMs), Machine Learning Operations, Agentic AI Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: We are looking for a highly skilled AI Engineer specializing in Generative AI and Multi-Agent Systems to design and deploy intelligent, autonomous solutions. This role focuses on building LLM-powered, agent-driven architectures that can reason, collaborate, and execute complex workflows across enterprise systems. You will work on cutting-edge Agentic AI frameworks, enabling systems that go beyond prediction to decision-making, orchestration, and autonomous execution. Roles & Responsibilities: - Design and build multi-agent AI systems capable of planning, reasoning, and task execution - Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestration - Implement Agentic workflows (planner - executor - critic - memory loops) - Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge grounding - Develop tool-using agents that integrate with APIs, databases, and enterprise systems - Architect and deploy AI copilots and autonomous assistants for business workflows - Optimize LLM performance using fine-tuning, prompt chaining, and caching strategies - Implement short-term and long-term memory mechanisms (vector stores, knowledge graphs) - Design multi-agent collaboration protocols (hierarchical, swarm, role-based agents) - Deploy scalable solutions using MLOps & LLMOps practices (monitoring, evaluation, guardrails) - Ensure AI safety, governance, and responsible AI practices Professional & Technical Skills: - Experience building multi-agent orchestration systems with role-based coordination - Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree of Thought) - Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfoo) - Knowledge of graph-based reasoning, knowledge graphs - Building autonomous systems or copilots in enterprise environments - Domain experience in industrial, energy, or IoT environments - Systems thinking for designing autonomous AI architectures - Strong problem decomposition for agent task design - Ability to balance latency, cost, and accuracy in LLM systems - Communication with business stakeholders to translate workflows into agent pipelines - Innovation mindset with focus on applying agentic AI in production - 3–8 years' experience in AI/ML with strong focus on Generative AI - Strong Python development skills - Hands-on experience with: - LLMs & GenAI frameworks - OpenAI, Hugging Face Transformers