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 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
- Robust 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

📌 LLM Operations Engineer (India)
🏢 Accenture
📍 India