Highlights:
10.00 – 15.00 Years
25.00 – 45.00 INR (Lacs)/Yearly
Full-time
Mumbai, Bengaluru, New Delhi
Skills
Agentic Ai
Roles & Responsibility
Basic Requirements
• Lead discovery workshops with business stakeholders to identify pain points, opportunities, and AI transformation use cases.
• Design and articulate end-to-end agentic solution for enterprise process/functional use-cases — the agent hierarchy, target-state agentic architecture, value streams, agent interation models and transformation roadmaps. (with technical depth and agentic system build experience in 1 platform or functional area – GCP, AWS, Snowflake, DataBricks, Azure, Anthropic)
• Assess enterprise data maturity, governance and technology readiness to shape scalable AI adoption.
• Lead solution definition across business, architecture, data, and engineering teams while ensuring end-to-end traceability from business value to implementation.
• Develop value framework for Agentic AI with the right industry/clinet context. Using the framework, build executive business cases including value estimation, investment requirements, KPIs, and benefits realization.
• Drive business readiness and change management by defining stakeholder engagement, communication, training, and adoption plans for AI transformation initiatives.
Good to Have
* Experience defining enterprise data strategies, data products, and AI-ready data foundations.
* Exposure to knowledge architecture, semantic layers, and enterprise knowledge management.
* Experience designing AI governance frameworks, operating models, and organizational readiness for AI adoption.
* Strong consulting, executive communication, stakeholder management, and problem-structuring skills with experience leading cross-functional delivery teams.
Requirements
Role Summary
• Min. 10 yrs overall, incl. AI & data projects
• High-value consulting; large-scale delivery with minimal oversight
• Has led at least one end-to-end process reengineering or reinvention engagement
• Process modelling and requirements definition at enterprise scale
• Manages senior stakeholders
• Awareness of AI governance and regulation (e.g., EU AI Act, model risk)
• Structured problem-solving; program management; strong communication
Qualifications & Certifications
- Bachelor’s degree (relevant discipline); MBA preferred
