AI Engagement Manager

Job Description

We are seeking a highly experienced AI/ML/GenAI Engagement Manager to lead large-scale AI transformation programs within the Insights & Data practice. This role requires a unique blend of deep technical expertise, hands-on development capability, and business leadership, including P&L ownership.

The ideal candidate will have proven experience in architecting and building AI/GenAI/Agentic AI solutions, driving production-grade deployments, and managing end-to-end client engagements.

Key responsibilities

Technical Leadership (Hands-on)

• Design, build, and code end-to-end AI/ML, GenAI, and Agentic AI solutions
• Contribute to architecture, prototyping, and development
• Develop scalable systems including:
• Data ingestion & processing pipelines
• Model training & inference layers
• LLM orchestration & prompt pipelines
• Vector databases & semantic search
• APIs, UI integration & deployment pipelines

Agentic AI & GenAI Delivery

• Build Agentic AI, conversational AI, chatbots, and AI assistants
• Implement RAG pipelines, multi-agent orchestration, and LLM-based applications
• Drive enterprise GenAI adoption and innovation

POC to Production

• Own end-to-end lifecycle from POC to production
• Deliver scalable, production-grade solutions balancing speed and robustness

Engagement & Delivery

• Manage AI/ML programs for global clients with delivery excellence
• Operate in fixed-price / outcome-based models
• Lead client engagements, CXO discussions, AI strategy, and thought leadership

Primary skills

Technical Expertise

• Hands-on experience in AI/ML, GenAI, and Agentic AI
• Strong Python skills with experience in Data science, Deep Learning, Agentic Frameworks like
• LangChain / LangGraph
• Semantic Kernel , AutoGen / CrewAI

• Workflow orchestration (state machines, DAGs)

• AIOps, MLOpsw, GraphDB, LLM Gateway, Guardrails.

Architecture & Systems

• Experience in end-to-end AI architecture design
• Knowledge of:
• LLM pipelines & orchestration
• Vector databases (Pinecone,Weaviate, Milvus etc)
• Distributed systems & scalable deployments

Data Expertise

• Strong background in Data Science (ML, NLP, GenAI) OR
  Data Engineering (large-scale data pipelines)
• Working knowledge of both preferred

Business & Delivery

• Experience managing AI programs with P&L responsibility (Good to have)
• Strong client-facing and stakeholder management skills (Must have)

Preferred domain- Telecom (good to have).