Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Industry Solutions Lead

Capgemini
London
6 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist - Industry Solutions Engineering

Machine Learning & AI Engineer

Machine Learning & AI Engineer

MLOps Engineer

MLOps Engineer

Data Engineer

Job Title:AI Industry Solutions Lead


Get The Future You Want!

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.


Your Role

The AI Industry Solutions Lead role lead will use our AI use case exploration approach combined with their own experience and knowledge to identify, scope and run these use case exploration projects working with stakeholders from across Capgemini and our customers. Specific responsibilities include:

  • Manages and successfully executes assigned AI use case explorations through the entire lifecycle
  • Collaborates with cross-functional partners from product, architecture, BD, Risk, Legal, Data Privacy, AI Governance etc. to achieve successful outcomes
  • Facilitates workshops to upskill key partners and teams on innovation mindset and methods
  • Working with the AIIS Manager, helps iterate on the AI use case exploration process to develop new methods and tools based on sprint experiences and our partner feedback
  • Continuously research and implement brand new AI and machine learning techniques to improve capabilities, ensuring Capgemini remains at the forefront of AI Innovation in the financial industry.


Your Profile

The ideal candidate will have 5-10 years of experience in innovation, AI, project planning in the financial services industry. Key attributes below:

  • A background of working in an agile product environment and/or experience applying design thinking principles in a product development context
  • Strong experience in analysing complex business problems and translating them into structured data science projects and AI powered solutions
  • Ability to operate in a fast-paced, ever-evolving technological landscape
  • Experience of sourcing and prioritising customer needs in a product development lifecycle
  • Excellent collaboration skills, communication skills, stakeholder management skills and ability to inspire and motivate others around shared goals
  • Strong organization and planning skills with the ability to prioritise workload when multiple projects are on the go
  • Entrepreneurial, creative and passionate about solving tough challenges
  • Relevant industry knowledge and experience in financial services, ideally banking, payments or securities
  • Brings a Consulting mindset to work with the customers to understand their challenges and address them using our frameworks and innovation toolkit
  • A can-do attitude and drive to achieve excellence in all the work they do.


About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse group of 350,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, cloud, and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.


Get The Future You Want |www.capgemini.com

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.