Information Technology Delivery Manager

Role Overview
We are looking for an experienced GenAI Delivery Lead who can drive end-to-end delivery of enterprise AI/ML and Generative AI programs while managing global stakeholders, large delivery teams, and strategic transformation initiatives.

The candidate should have strong experience in:
Enterprise Delivery Management
AI/ML & GenAI Program Execution
Client Engagement & Governance
Solution Delivery & Transformation
Cross-functional Team Leadership
Exposure to Agentic AI, Multi-Agent Systems, RAG, LLMOps, AI Governance, and AI Platforms will be an added advantage.

Key Responsibilities: -
Lead enterprise-scale AI/ML and Generative AI transformation programs
Drive end-to-end delivery governance including planning, execution, risk management, budgeting, and stakeholder communication
Manage global delivery teams across AI Engineers, Data Scientists, Architects, MLOps, and Product stakeholders
Partner with CXOs, business leaders, and clients to define AI transformation roadmaps
Oversee implementation of GenAI use cases including:
RAG-based systems
LLM-powered enterprise applications
AI Assistants & Conversational AI
Intelligent Automation platforms
Predictive Analytics & Decision Intelligence
Ensure scalable and secure AI solution delivery across cloud ecosystems (Azure/AWS/GCP)
Drive delivery excellence, SLA adherence, quality governance, and operational efficiency
Collaborate with presales and solution teams for RFPs, proposals, estimations, and AI solutioning.
Establish AI delivery best practices, governance frameworks, and reusable accelerators
Mentor teams and build high-performing AI delivery organizations
Required Skills & Experience
Mandatory:
15+ years of overall Technology Delivery exposure
Strong experience in Delivery Leadership / Program Management / AI Transformation
Hands-on exposure to AI/ML and Generative AI ecosystems
Experience managing enterprise-scale transformation programs
Strong stakeholder management and client-facing experience
Experience handling global teams and multi-vendor environments
Good understanding of:
LLMs
RAG Architectures
AI/ML Platforms
NLP / Predictive Analytics
MLOps / LLMOps concepts
Exposure to Cloud Platforms:
Azure
AWS
GCP
Experience in Agile / SAFe / DevOps delivery models
Good to Have:
Agentic AI / Multi-Agent Systems
LangChain / LangGraph / CrewAI / AutoGen
AI Governance & Responsible AI
AI CoE / Practice Building
Pre-sales / GTM / AI Consulting exposure
BFSI / Telecom / Retail / Healthcare domain experience