Head Of Artificial Intelligence

Role

The Head of AI will be responsible for defining and executing Tata Consulting Engineers enterprise-wide AI strategy, driving both internal transformation and external digital business growth.

This role will lead the creation of an AI-first, agentic enterprise, embedding AI across the full value chain (sales, engineering, delivery, HR, finance, legal, and proposals), while also building a market-facing Industrial AI portfolio aligned with TCEs Digital Twin strategy.

The role combines vision, execution, productization, and monetization, with accountability for delivering measurable business outcomes including productivity gains, faster project delivery, and new revenue streams (ARR-based AI products and platforms).

Key Responsibilities

1. Enterprise AI Transformation (Internal Focus)

• Define and execute TCEs roadmap to become an AI-native, agentic enterprise
• Drive AI adoption across core business functions:
• Engineering & design automation
• Sales & proposal intelligence
• Project delivery optimization
• HR, finance, legal process automation
• Build AI awareness and capability across the organization, including leadership alignment and workforce upskilling
• Establish AI governance, ethics, and responsible AI frameworks
• Lead development of enterprise AI copilots and agents to improve productivity and decision-making
• Deliver measurable outcomes:
• Reduction in project cycle times
• Increased engineering efficiency
• Improved win rates and margins

2. Industrial AI Business (External / Revenue Focus)

• Build TCEs Industrial AI capability as part of the Digital Business Unit
• Define and launch AI-led offerings integrated with Digital Twin solutions
• Create a scalable Industrial AI backbone/platform aligned with:
• Simulation-driven design
• Smart infrastructure
• Asset lifecycle intelligence
• Develop AI-powered products and solutions targeting industries such as:
• Infrastructure & urban development
• Energy & utilities
• Manufacturing & industrial plants
• Drive productization and monetization:
• Build ARR-based AI products/platforms
• Define pricing, packaging, and GTM strategy
• Lead customer engagements for AI-led transformation programs
  

3. AI Platform & Product Leadership

• Oversee development of TCEs AI platform architecture
• Data pipelines, model lifecycle, orchestration layers
• Integration with digital twin environments
• Guide AI Product Manager in building scalable, reusable AI products
• Ensure alignment between:
• Platform capabilities
• Business use cases
• Market needs

4. Ecosystem & Partnerships

• Build and manage strategic partnerships with:
• Hyperscalers and AI platforms
• Industrial AI and simulation players
• Startups and academia
• Leverage partnerships to accelerate:
• Capability building
• Joint GTM initiatives
• Innovation and co-development
• Position TCE as a thought leader in Industrial AI and Digital Twin convergence

5. Innovation & Thought Leadership

• Establish TCE as a leader in:
• Agentic AI in engineering and infrastructure
• AI + Digital Twin convergence
• Drive innovation programs, PoCs, and pilots
• Represent TCE in industry forums, client discussions, and strategic engagements

Key Focus Areas (Critical Success Priorities)

Year 1 Priorities

• Establish AI governance, operating model, and roadmap
• Launch 3–5 high-impact internal AI use cases (quick wins)
• Build foundational AI platform and data readiness
• Define and pilot Industrial AI offerings
• Create initial AI product portfolio roadmap

Medium-Term (2–3 Years)

• Transition TCE into a scaled AI-enabled enterprise
• Launch commercial AI products with ARR revenue streams
• Deep integration of AI into Digital Twin solutions

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• Build a strong AI talent and capability pipeline

Candidate Profile

Experience

• 15+ years of experience in AI, data, or digital transformation
• Proven track record of:
• Scaling AI initiatives in enterprises
• Building AI products/platforms
• Driving business impact through AI
• Experience in industrial sectors (EPC, infrastructure, manufacturing, energy) strongly preferred
• Exposure to Digital Twin, simulation, or engineering systems is a strong advantage

Technical & Functional Expertise

• Strong understanding of:
• AI/ML, GenAI, and Agentic AI architectures
• Enterprise AI platforms and MLOps
• Data strategy and governance
• Experience in building:
• AI-driven products
• Scalable platforms
• Enterprise-wide AI adoption frameworks

Leadership & Behavioral Competencies

• Strategic thinker with execution rigor
• Ability to bridge technology, engineering, and business
• Strong stakeholder management (CxO-level influence)
• Entrepreneurial mindset with focus on value creation and monetization
• Proven ability to build and lead high-performing teams

Key Success Metrics

• AI adoption across business functions (% coverage)
• Productivity and efficiency improvements
• Revenue from AI-led offerings (ARR contribution)
• Number of AI products successfully launched
• Customer impact and satisfaction from AI solutions
• Strength of AI ecosystem partnerships

Why This Role is Critical

This role sits at the intersection of engineering excellence, digital innovation, and business transformation, and will define how TCE evolves into:

• An AI-first engineering enterprise
• A leader in Industrial AI + Digital Twin solutions
• A platform-led digital business with recurring revenue streams