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About the Role

You will own the platform that Claims, Payments, and Health run on, acting as its first and most senior engineer-leader. This involves managing the agentic AI floor, including the model gateway, agent runtime, evaluation infrastructure, and guardrails, as well as shared product services like case management, work queues, integration connectors, multi-tenancy, and metering. Your work directly supports the automation of claims handling and payment processing.

Responsibilities

Own the strategic vision, roadmap, and end-to-end lifecycle of the platform, from model gateway and agent runtime to shared workflow, tenancy, and metering services.
Develop and maintain a competitive engineering strategy at the AI frontier, tracking research and model releases to guide platform adoption and development.
Manage closed improvement loops, ensuring production signals and evaluation verdicts feed into reinforcement learning and fine-tuning pipelines for LLMs and SLMs.
Make build-vs-buy decisions for AI infrastructure, defining the boundary between platform-provided services and product line development.
Implement a disciplined operating model with a published capacity split for product team requests, platform quality, and strategic initiatives.
Ensure platform adoption outcomes are measured by consumer delivery metrics.
Maintain the platform's compliance posture in regulated environments, including model risk documentation, audit trails, and responsible AI practices.
Hire and grow the platform group, setting engineering standards for the organization.

Requirements

Track record leading platform or infrastructure teams with production systems serving multiple product teams, accountable for adoption.
Hands-on credibility in modern AI infrastructure: LLM inference and serving, model gateways, vector search, guardrails, and evaluation systems.
Fluency in frontier research, including post-training, reinforcement learning, and agentic systems, with the ability to translate research into engineering strategy.
Deep cloud platform knowledge (AWS, Azure, or GCP) with production-scale Kubernetes and infrastructure-as-code.
Experience delivering in a regulated industry (ideally financial services) or demonstrable fluency in model risk and security review requirements.
A platform-as-product mindset, comfortable discussing golden paths, voluntary adoption, and developer research.
Daily, hands-on use of AI coding assistants.

Skills

LLM inference and serving
Model gateways
Vector search
Guardrails
Evaluation systems
Post-training AI
Reinforcement learning
Agentic systems
Cloud platforms (AWS, Azure, GCP)
Kubernetes
Infrastructure-as-code
Platform-as-product
AI coding assistants

Experience Level

Senior engineer-leader

Benefits

Range of core and flexible benefits
Peer Recognition Portal called Applaud
Accredited Great Place to work for Wellbeing in 2024
Mental Health Champions
Wellbeing apps such as Thrive and Peppy
Countless training and development opportunities
Access to 250,000 courses with numerous external certifications

About the Company

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value.
We imagine the future of organisations and make it real with AI, technology and people.
We have a strong heritage of nearly 60 years and are a responsible and diverse group of 420,000 team members in more than 50 countries.
We deliver end-to-end services and solutions with deep industry expertise and a strong partner ecosystem, leveraging capabilities across strategy, technology, design, engineering, and business operations.
The Group reported 2024 global revenues of €22.1 billion.

Equal Opportunity

Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme.
As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role.
Please opt in during the application process.