S&C Global Network - AI - CDI -Agentic AI- Manager

Accenture; India; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Accenture is seeking an AI Decision Science Manager to lead the strategy, architecture, delivery, and adoption of enterprise-scale Generative AI and Agentic AI solutions. You will define AI roadmaps, lead cross-functional teams, and engage with senior client stakeholders to deliver production-grade platforms.

You will drive enterprise AI transformation by combining LLMs, Multi-Agent Systems, MCP, RAG, and cloud-native architectures with enterprise integrations and Security/Observability

Qualifications

• Minimum 7 years of experience in AI/ML with demonstrated enterprise Generative AI and Agentic AI leadership.
• Proven track record delivering cross-functional AI programs and client engagements.
• Strong experience in solution architecture and governance for enterprise AI.

Responsibilities

• Own end-to-end delivery of enterprise AI programs from strategy through production deployment.
• Define AI architecture, delivery roadmap, governance, and technical standards.
• Lead multidisciplinary AI engineering teams and mentor consultants and analysts.
• Drive delivery excellence, quality, risk management, and client satisfaction.
• Engage with senior client stakeholders to define roadmaps and outcomes.
• Oversee integration with enterprise systems and data platforms.

Skills

Generative AI

Agentic AI Systems

Large Language Models

Model Context Protocol

Multi-Agent Systems

AI Agent Orchestration

Python

SQL

Machine Learning

LangGraph

AI Refinery

Azure AI Foundry

Azure OpenAI

Retrieval-Augmented Generation

Prompt Engineering

Function Calling

Tool Calling

REST APIs

LLM Fine-tuning

AI Model Evaluation

Enterprise AI Architecture

Solution Architecture

Education

Bachelor's degree in Computer Science/Artificial Intelligence/related

Master's degree in Computer Science/Artificial Intelligence/related

Tools

LangChain

LlamaIndex

AutoGen

CrewAI

Semantic Kernel

Azure AI Search

Azure Functions

Microsoft Graph API

ServiceNow Integration

Splunk

Microsoft Teams Integration

Vector Databases

Docker

Kubernetes

Azure DevOps

CI/CD

MLOps

AI Guardrails

Responsible AI

AI Evaluation Frameworks

Observability

Git

Job description

AI Decision Science Manager - Updated Job Description

Job Title

Ind & Func AI Decision Science Manager – Agentic AI & Enterprise Intelligence

Management Level

7 – Manager

Location

Open

Must Have Skills

Generative AI, Agentic AI Systems, Large Language Models (LLMs), Model Context Protocol (MCP), Multi-Agent Systems, AI Agent Orchestration, Python, SQL, Machine Learning, LangGraph, AI Refinery, Azure AI Foundry, Azure OpenAI, Retrieval-Augmented Generation (RAG), Prompt Engineering, Function Calling, Tool Calling, REST APIs, LLM Fine-tuning, AI Model Evaluation, Enterprise AI Architecture, Solution Architecture

Good to Have Skills

LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, Azure AI Search, Azure Functions, Microsoft Graph API, ServiceNow Integration, Splunk, Microsoft Teams Integration, Vector Databases, Docker, Kubernetes, Azure DevOps, CI/CD, MLOps, AI Guardrails, Responsible AI, AI Evaluation Frameworks, Observability & Monitoring, Git, Cloud Platforms (Azure, AWS, GCP)

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.

Educational Qualification

Bachelor's or Master's degree (BE/BTech/MTech/MS/MBA) in Computer Science, Artificial Intelligence, Machine Learning, Information Technology, Data Science, Mathematics, Statistics, or related disciplines with an excellent academic record.

Job Summary

As an AI Decision Science Manager, you will lead the strategy, architecture, delivery, and adoption of enterprise-scale Generative AI and Agentic AI solutions. You will define AI roadmaps, lead cross-functional delivery teams, engage with senior client stakeholders, and oversee the successful implementation of production-grade AI platforms. You will drive enterprise AI transformation by combining LLMs, Multi-Agent Systems, MCP, RAG, and cloud-native architectures with enterprise integrations including ServiceNow, Microsoft Graph, Teams, Splunk, Azure AI Services, and business applications.

Roles & Responsibilities

Strategic Leadership & Delivery

• Own end-to-end delivery of enterprise AI programs from strategy through production deployment.
• Define AI architecture, delivery roadmap, governance, and technical standards.
• Lead multidisciplinary AI engineering teams and mentor consultants and analysts.
• Drive delivery excellence, quality, risk management, and client satisfaction.

Client & Stakeholder Engagement

• Act as trusted advisor to executive stakeholders on AI strategy and adoption.
• Lead workshops, solutioning sessions, architecture reviews, and executive presentations.
• Support business development, proposals, PoCs, and AI transformation initiatives.

Agentic AI & LLM Engineering

• Lead development of enterprise AI agents using AI Refinery, LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, and custom architectures.
• Oversee LLM fine-tuning, evaluation, prompt engineering, MCP implementation, and multi-agent orchestration.
• Drive reusable AI frameworks, accelerators, and enterprise standards.

Enterprise AI Integration

• Lead integrations with ServiceNow, Microsoft Graph API, Microsoft Teams, Splunk, Azure Functions, Azure SQL, and REST APIs.
• Define enterprise integration, security, authentication, and observability standards.

AI Governance & Quality

• Establish Responsible AI, guardrails, evaluation frameworks, security, compliance, and operational governance.
• Monitor AI quality, business KPIs, costs, latency, hallucinations, and production health.

Innovation & Capability Development

• Drive AI innovation, capability building, reusable assets, mentoring, and knowledge sharing.
• Stay current with emerging AI technologies and define adoption strategy.

Professional & Technical Skills

Must Have

Generative AI, Agentic AI Systems, Large Language Models (LLMs), Multi-Agent Systems, Model Context Protocol (MCP), AI Agent Orchestration, Python, SQL, Machine Learning, LangGraph, AI Refinery, LangChain, Prompt Engineering, Function Calling, Tool Calling, Retrieval-Augmented Generation (RAG), LLM Fine-tuning, AI Model Evaluation, Enterprise AI Architecture, Solution Architecture

Cloud & Infrastructure

Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure DevOps, Docker, Kubernetes, CI/CD, MLOps, Git

Enterprise AI Technologies

ServiceNow, Microsoft Graph API, Microsoft Teams, Splunk, Azure SQL, Vector Databases, Semantic Search, Enterprise API Integration, MCP Servers, AI Guardrails, AI Observability, Human-in-the-Loop (HITL)

Preferred Qualifications

• Proven experience leading enterprise AI and Agentic AI delivery programs.
• Strong executive stakeholder management and consulting experience.
• Experience defining enterprise AI architecture, governance, and operating models.
• Experience managing large cross-functional delivery teams.
• Strong understanding of Responsible AI, AI security, compliance, and enterprise-scale deployments.

Equal Employment Opportunity Statement

All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

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