About the RoleWe are seeking a visionary Group AI Lead to drive enterprise-wide AI and advanced analytics initiatives across the Operations domain. This is a senior leadership role for a seasoned AI professional who operates at the intersection of cutting-edge technology, ethical AI, and measurable business impact.
You will lead the design, development, and deployment of scalable, high-impact AI solutionsspanning traditional ML, Generative AI, and Agentic AIwhile championing Responsible AI practices across the organization.
As the Group AI Lead, you will own end-to-end AI solution design in alignment with the Group Solution Blueprint, AI architecture standards, Responsible AI principles, and cost governance frameworks. You will also coordinate solution rollout across Local Business Units (LBUs), balancing global consistency with local regulatory and business requirements.
This role serves as the central orchestration point between Group AI solution owners and LBU AI teams and acts as a trusted partner to senior leaders across Technology, Data, and Operations. You will enable scalable AI adoption across key operational pillars such as Claims Management, New Business Underwriting, CRM platforms, and Digital Servicing.
Key Responsibilities1. Group-Level AI Solution Design- Translate strategic business objectives into actionable AI and data science requirements.
- Lead AI initiatives for Group-wide solutions in collaboration with Pillar workstream leads, LBU AI leads, and cross-functional teams.
- Architect reusable traditional, Generative, and Agentic AI solutions using a mix of off-the-shelf and custom-built technologies.
- Evaluate vendor AI solutions for performance, cost efficiency, scalability, and reusability.
- Define AI integration points across business processes and translate them into technical architectures in partnership with Engineering and Enterprise Architecture teams.
- Specify structured and unstructured data requirements in collaboration with Data Leads.
- Develop AI implementation roadmaps considering data readiness, AI asset availability, and resourcing needs.
- Build AI solution prototypes where required to accelerate LBU adoption and localization.
2. AI Solution Build & Implementation- Coordinate closely with LBU AI teams during implementation of Group-level AI solutions.
- Enable local customization while ensuring adherence to global design standards across the full AI lifecycle, including:
- Feature engineering
- Model and LLM selection
- Bias, fairness, and robustness testing
- System integration and validation
- Augment LBU execution capacity through internal resource allocation or vendor partnerships.
- Ensure standardized testing and timely submissions for AI Governance and Responsible AI approvals.
3. Testing, Deployment & Lifecycle Management- Oversee User Acceptance Testing (UAT), validating performance, fairness, and cost assumptions.
- Manage deployment of AI solutions into production platforms in line with the Group Solution Blueprint.
- Ensure performance, cost, and drift monitoring dashboards are implemented with strong feedback loops for continuous improvement.
- Conduct periodic cross-LBU reviews to identify optimization, enhancement, and reuse opportunities.
4. Team Leadership & Capability Building- Lead, mentor, and develop a high-performing team of data scientists and AI engineers.
- Foster a culture of collaboration, innovation, and engineering excellence.
- Ensure adequate AI capability and capacity through strategic hiring and vendor partnerships.
Key Skills & Experience
Education
- Master's or PhD in Data Science, Computer Science, AI, or a related quantitative field
Experience
- 10+ years of experience in AI/Data Science (Master's) or 7+ years post-PhD
- 3+ years leading and managing AI/Data Science delivery teams
Programming & Tools
- Strong hands-on experience with Python and SQL
- Experience with LangChain, Hugging Face, and modern LLM frameworks
AI Use-Case Deployment (minimum 3 required)
- Conversational AI/chatbots using LLMs for intent detection
- AI enablement for CRM systems (e.g., Next Best Action, personalization)
- AI-based routing and decisioning systems
- Sentiment analysis and customer insights
- Voice transcription, audit, and quality monitoring
- Fraud, Waste & Abuse detection
- LLM-based OCR and Intelligent Document Processing
Cloud & Platforms
- Hands-on experience with Azure or Google Cloud platforms
MLOps / AIOps
- Experience managing ML/LLM artifacts, deployments, and cost optimization is a strong plus
Stakeholder & Leadership Skills
- Proven experience engaging C-suite stakeholders and translating strategy into enterprise AI roadmaps
- Exceptional communication skills across technical and non-technical audiences
Commercial & Strategic Acumen
- Strong ability to translate AI performance into tangible business and financial outcomes
- Proven track record of designing AI solutions with clear ROI and cost governance
Collaboration & Problem Solving
- Strong cross-functional and cross-geography collaboration skills
- Demonstrated critical thinking, structured problem-solving, and analytical rigor