Head of Agentic AI
Role Purpose
The Head of Agentic AI is a strategic innovation leader responsible for pioneering the transition from Generative AI to Autonomous Agentic Systems. This role owns the Agentic AI Framework (Orchestration, RAG, MCP), enabling agents to execute complex workflows. Crucially, this role also acts as the "Chapter Lead" for the AI Factory—managing a large pool of high-skilled AI experts allocated to deliver products and use cases across the group. This is a role combining cutting-edge technical architecture with large-scale resource and delivery management.
Key accountabilities and decision ownership:
● Agentic AI Platform: Deliver reusable Agentic AI platform frameworks and accelerators.
● AI Factory Management: Lead and develop a "Chapter" of high-skilled AI experts (ML Engineers, AI Engineers), allocating them dynamically to Product Teams (e.g., Super Tobi, AI Products) based on demand.
● Agentic AI Strategy Delivery: Define and execute the roadmap for autonomous agents, multi-agent systems, and the "Agentic Framework"
● Delivery of RAG, GraphRag, Knowledge Management and MCP.
● Innovation & Value Creation: Prototype and industrialize high-complexity AI use cases that leverage reasoning and autonomy to generate new revenue streams or massive efficiencies.
● Architecture Evolution: Transform the architecture from static models to dynamic, context-aware agent ecosystems that can integrate with enterprise systems.
● Consulting & Delivery: Adopt a "consultancy mindset" to understand complex business problems from C-level stakeholders and deploy the right agentic solutions to solve them.
Key performance indicators :
- Adoption of Agentic AI platform / Value generated by Agentic AI use cases.
- Value generation of the AI Factory talent pool.
- Successful deployment of re-usable Agentic components (reducing dev time for future agents).
- Time to market Delivery
Core competencies, knowledge and experience:
● Visionary Leadership: Ability to conceptualize and build "Next Gen" AI solutions (Agents, Reasoning) before they are market standards (with an R&D mindset).
● Resource Management: Experience managing large, high-skill technical teams (Chapters) in a matrix/agile organization (50+ people).
● Data Intensive Integration: Strong background in complex data integration, RAG architecture, GraphRAG and semantic search.
● Commercial Acumen: Ability to frame technical innovations as business value propositions for internal and external customers.
● Stakeholder Management: Experience presenting complex AI concepts to non-technical C-suite executives. Experience in managing and prioritizing different and conflictual needs.
● Vendor & Partner Management: leveraging Microsoft/Google partnerships and third party integrators.
Must have technical / professional qualifications:
● Degree and Postgraduate degrees in Computer Science, Artificial Intelligence, or Mathematics Engineering.
● Proven Experience in AI & Data for Telco
● Hands-on experience with LLM frameworks (e.g., ADK, LangChain, LiteLLM), Vector Embeddings, Vector and Graph Databases (e.g. Cloud Spanner).
● Proven experience delivering Data Intensive applications and APIs.
● Experience in a highly complex enterprise, or consulting or professional services environment, is highly desirable.
● Hands-on experience in Google Cloud Platform
● Experience in managing distributed engineering teams
● Proven Experience in delivering AI Agents