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 - Solid 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.

📌 LLM Operations Engineer (Pune)
🏢 Accenture in India
📍 Pune