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

Accenture -
Gurugram, Haryana

Apply Now

Job details

Full-time
14 hours ago

Qualifications

CI/CD
Cloud infrastructure
Azure
Law
Computer Science
MCP
Kubernetes
Git
Master's degree
SQL
OS Kernels
AWS
Docker
Bachelor's degree
Machine learning
Continuous integration
Splunk
REST
APIs
ServiceNow
B.E.
Business Administration
Data science
Solution architecture
AI
MBA
Python

Full 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.

Apply Now

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