LLM Operations Engineer
Accenture
- Location
- Onsite (Bengaluru, Karnataka)
- Employment
- Full-time
- Level
- Senior Level
Posted 6 days ago
About the Role
Accenture seeks an LLM Operations Engineer to design and deploy multi-agent AI systems and RAG pipelines for enterprise workflows. This role focuses on building autonomous, agent-driven architectures that reason, collaborate, and execute complex tasks using cutting-edge Generative AI technologies.
Skills
Generative AI
Large Language Models
Machine Learning Operations
Agentic AI
Python
LangChain
AutoGen
CrewAI
Semantic Kernel
RAG pipelines
Vector databases
Prompt engineering
Docker
Kubernetes
CI/CD pipelines
Azure OpenAI
Full job details
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
- 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
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
- 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
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
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