1. AI Product Strategy & Roadmap

• Define and own the AI product vision, roadmap, and backlog.

• Identify use cases that deliver measurable business value.

• Prioritise AI initiatives based on ROI, business impact, complexity, and risk.

• Align AI initiatives with strategic business objectives.

• Create business cases and value-realisation frameworks

2. AI Solution Design

Work closely with engineers, architects, and data scientists to define:

• AI workflows

• Agent orchestration, Design multi-agent workflows for insurance processes.

• Prompt engineering requirements

• RAG architecture requirements, Design enterprise RAG architectures

• Human-in-the-loop controls

• Explainability requirements

• Decision-making workflows

3. Technical Leadership

Provide technical leadership in following areas

• LLMs and GenAI architecture

• Agentic AI frameworks and components such as Langraph, Transformer and MCP

• RAG architectures

• Prompt engineering

• Vector databases

4. Data & AI Governance

Ensure adherence to:

• Responsible AI principles

• Model governance

• AI explainability

• Regulatory compliance

• Data privacy requirements

• AI risk management

Establish processes for:

• Model monitoring

• Drift detection

• Prompt governance

• Auditability

• Human review processes

5. Adoption & Change Management

• Drive business adoption.

• Define KPIs and success measures.

• Measure realised business benefits.

• Conduct training and enablement activities.

• Partner with business leaders to embed AI into operating processes

Desired Candidate Profile

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related discipline.

• Master's degree preferred.

Experience

• 8–12 years of experience in Product Management, Digital Transformation, Technology Delivery, or AI Solutions.

• Minimum 5 years within Insurance.

• Proven experience implementing enterprise AI solutions.

Required Technical Skills

AI & Generative AI

Must Have

• Large Language Models (LLMs)

• Prompt Engineering

• Retrieval Augmented Generation (RAG)

• Agentic AI concepts

• AI orchestration frameworks

• AI evaluation methodologies

• Conversational AI

• AI governance