S&C Global Network - AI - CDI -Agentic AI- Manager
Heavy focus on building agentic AI and LLM-based systems—lots of agent orchestration, LangChain/AutoGen, RAG, and enterprise AI tooling.
About the Role
Lead strategy, architecture, delivery, and adoption of enterprise-scale Generative AI and Agentic AI solutions at Accenture. Define AI roadmaps and governance, manage cross-functional delivery teams, engage senior clients, and oversee production-grade AI platforms integrating LLMs, multi-agent systems, cloud services, and enterprise applications.
Job Description
Role
As an AI Decision Science Manager (Agentic AI & Enterprise Intelligence) you will lead the strategy, architecture, delivery, and adoption of enterprise-scale Generative AI and Agentic AI solutions. You will define AI roadmaps, technical standards and governance, lead cross-functional teams, engage senior stakeholders, and oversee implementation of production-grade AI platforms.
Key Responsibilities
- Own end-to-end delivery of enterprise AI programs from strategy through production deployment.
- Define AI architecture, delivery roadmaps, governance, and technical standards.
- Lead and mentor multidisciplinary AI engineering teams, consultants, and analysts.
- Act as a trusted advisor to executive stakeholders; run workshops, solutioning sessions, architecture reviews, and executive presentations.
- Support business development, proposals, and proofs-of-concept (PoCs).
- Lead development of enterprise AI agents and multi-agent orchestration, including LLM fine-tuning, prompt engineering, Function/Tool Calling, and Model Context Protocol (MCP) implementation.
- Drive integrations with enterprise systems (ServiceNow, Microsoft Graph, Teams, Splunk), cloud services, and REST APIs.
- Establish Responsible AI practices, guardrails, evaluation frameworks, observability, security, and operational governance.
- Monitor AI quality, KPIs, costs, latency, hallucinations, and production health.
Qualifications & Experience
- Minimum 7 years of experience in AI/ML with demonstrated expertise leading enterprise Generative AI and Agentic AI programs, managing delivery teams, solution architecture, and client engagements.
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, IT, Data Science, Mathematics, Statistics, or related discipline.
- Strong consulting experience with executive stakeholder management and large cross-functional team leadership.
- Experience defining enterprise AI architecture, governance, operating models, and Responsible AI practices.
Required Skills & Technologies
- Generative AI, Agentic AI systems, Large Language Models (LLMs), Multi-Agent Systems
- Model Context Protocol (MCP), AI Agent Orchestration, Retrieval-Augmented Generation (RAG)
- Python, SQL, Machine Learning, Prompt Engineering, Function Calling, Tool Calling, LLM Fine-tuning, AI Model Evaluation
- LangGraph, AI Refinery, LangChain
- Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure DevOps, Azure SQL
- REST APIs, Enterprise API Integration, Vector Databases, Semantic Search
- Docker, Kubernetes, CI/CD, MLOps, Git
Good to Have / Preferred
- Familiarity with LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel
- Microsoft Graph API, ServiceNow integration, Microsoft Teams integration, Splunk
- Experience with AI Guardrails, Responsible AI frameworks, observability & monitoring, human-in-the-loop (HITL)
- Cross-cloud exposure (Azure, AWS, GCP)
Notes
- Location: listed as “Open” in the posting.
- The description focuses on enterprise-scale delivery, architecture, integrations, governance, and operationalizing agentic AI solutions.