About this role
Accenture seeks an AI Decision Science Analyst – Agentic AI & Intelligent Automation (management level 11) in Gurugram. The analyst will design, develop, evaluate and deploy enterprise AI applications built on large language models, AI agents and multi-agent systems, working with architects, product owners, engineers and business stakeholders across industries.
Responsibilities
- Build agents that reason, plan, collaborate and execute business workflows; develop reusable orchestration components, AI copilots, human-in-the-loop approval workflows and Model Context Protocol (MCP) servers and integrations.
- Fine-tune and optimize LLMs; develop applications using prompt engineering, structured outputs, function calling and tool calling. Evaluate accuracy, latency, grounding, safety, hallucination rates and business outcomes through evaluation pipelines.
- Build retrieval-augmented generation solutions, including document ingestion, chunking, metadata enrichment, indexing, semantic search and retrieval-quality improvements.
- Integrate agents with enterprise systems including ServiceNow, Microsoft Graph, Microsoft Teams, Splunk, Azure Functions, Azure SQL and REST APIs. Address authentication, logging, retries and error handling.
- Implement AI guardrails, Responsible AI and governance controls; monitor agent execution, token use, workflow performance, cost and operational health. Participate in architecture and code reviews, testing, deployment, production support, CI/CD and MLOps. Document solutions, develop reusable accelerators and mentor junior colleagues.
Qualifications
A minimum of 2 years of AI/ML experience with demonstrated expertise in generative AI, LLMs, agentic AI, multi-agent systems and enterprise AI application development is required. A bachelor's or master's degree (BE/BTech/MTech/MS/MBA) in computer science, AI, machine learning, IT, data science, mathematics, statistics or a related discipline, with an excellent academic record, is specified. The posting lists Python, SQL, LangGraph, AI Refinery, Azure AI Foundry and Azure OpenAI among must-have skills. Experience deploying production-grade AI in a consulting or enterprise environment is preferred. Good-to-have skills include LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, Azure AI Search, vector databases, Docker, Kubernetes, Azure DevOps, Git and cloud platforms including Azure, AWS and GCP.