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, Machine Learning Operations, Large Language Models (LLMs), Agentic AI

• *Good to have skills :** NA

Minimum **3** 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

• Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kernel

\- RAG pipelines \& vector DBs\- FAISS, Pinecone, Weaviate

• Experience building API\-driven, tool\-integrated AI agents

\- Strong understanding of \-

• Prompt engineering \& prompt optimization
• Chain\-of\-thought reasoning and tool augmentation
• Context management and token optimization
• Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptable)
• Knowledge of Docker, Kubernetes, CI/CD pipelines

Additional Information

• The candidate should have minimum 3 years of experience in Generative AI.
• This position is based at our Pune office.
• A 15 years full time education is required.

15 years full time education