About this role
Accenture seeks an AI Decision Science professional to design, develop and deploy autonomous AI agents and multimodal solutions for complex business workflows. The posting identifies the position internally as “Ind & Func AI Decision Science Analyst - S&C GN” at management level 11 (Analyst). It is a full-time role based at the Gurugram office; the listing states 5–10 years of experience.
Responsibilities
- Design AI agents and multi-agent systems that reason, plan, collaborate and execute workflows, using agentic frameworks and custom architectures. Implement Model Context Protocol (MCP) connections to external tools and APIs.
- Build and deploy generative AI applications and AI models. Develop solutions using computer vision, machine learning and LLMs; train and fine-tune LLMs on large-scale datasets, evaluate performance and make iterative improvements.
- Define data requirements; clean, aggregate, analyze and interpret data; and assess data quality. Integrate scalable AI solutions into end-to-end workflows and use cloud platforms for development and deployment.
- Explore advances in AI and data science, and document methods and findings for knowledge sharing.
Requirements and additional skills:
- Must-have expertise in generative AI, agentic AI systems, MCP, LLMs, multi-agent systems, Python, SQL and AI agent orchestration frameworks.
- The posting also seeks experience building AI/ML models and autonomous systems for complex business workflows, understanding of AI safety, alignment and governance, and experience with enterprise AI agent deployments and production systems.
- Listed good-to-have skills include AI Refinery, LangChain, LlamaIndex, AutoGen, CrewAI, Spark, AWS, Azure, GCP, NLP, computer vision, vector databases, RAG, function calling and tool integration. Other listed technical areas include Docker, Kubernetes, MLOps pipelines, reinforcement learning for agent training and multimodal AI.
Skills for this role
Generative AIAgentic AIModel Context Protocol (MCP)Large Language Models (LLMs)Multi-Agent SystemsPythonSQLAI Agent OrchestrationAI RefineryLangChainLlamaIndexAutoGenCrewAISparkAWSAzureGCPNatural Language ProcessingComputer VisionVector DatabasesRetrieval-Augmented GenerationFunction CallingTool IntegrationDockerKubernetesMLOpsReinforcement LearningMultimodal AIMachine LearningData Science