At a Glance
- Tasks: Lead the design and deployment of innovative AI solutions in financial services.
- Company: Join Capgemini, a global leader in AI-powered business transformation.
- Benefits: Enjoy hybrid working, competitive salary, and extensive training opportunities.
- Other info: Be part of a diverse team committed to ethical practices and employee wellbeing.
- Why this job: Make a real impact by shaping the future of AI in finance.
- Qualifications: 10+ years in AI architecture with hands-on experience in enterprise solutions.
The predicted salary is between 72000 - 88000 £ per year.
We are seeking a highly experienced Lead AI Architect to drive the design, architecture, and deployment of enterprise-scale AI solutions within regulated financial services environments. This role will combine strategic architecture leadership with hands-on technical delivery, helping clients transition AI initiatives from proof-of-concept to robust, scalable, and governed production solutions. The successful candidate will define reusable AI engineering foundations, establish architecture standards, and lead complex client engagements across Banking, Insurance, and Capital Markets. They will work closely with engineering, data, risk, compliance, and executive stakeholders to ensure AI systems are explainable, secure, cost-effective, and compliant with regulatory expectations.
Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:
- AI Solution Architecture & Delivery: Lead the architecture, design, and implementation of enterprise AI and Generative AI solutions within regulated financial services organizations.
- Partner with client engineering, data, security, and risk teams to operationalize AI solutions and move them into production environments.
- Define end-to-end AI architecture covering data ingestion, retrieval, orchestration, model serving, governance, and monitoring.
- Design scalable AI/ML platforms leveraging cloud-native services and modern data architectures.
- Ensure AI solutions operate within agreed governance, security, and compliance frameworks.
- Conduct architecture reviews and provide technical leadership throughout project lifecycle.
- Lead technical workshops, demonstrations, and architecture discussions with CIOs, CTOs, CDOs, Risk Leaders, and Engineering Teams.
Data, Context & Control Architecture:
- Design robust data foundations supporting AI workloads, including semantic layers, knowledge graphs, vector databases, and retrieval systems.
- Establish architectures that ensure AI models leverage trusted and governed enterprise data.
- Define data lineage, traceability, and auditability requirements for AI-driven business processes.
- Implement architecture patterns supporting explainability, transparency, and responsible AI adoption.
AI Governance, Evaluation & Observability:
- Develop frameworks for AI model evaluation, validation, monitoring, and continuous improvement.
- Define standards for model performance testing, bias detection, hallucination management, and output quality assessment.
- Implement observability frameworks using industry-leading tools and OpenTelemetry-based tracing.
- Establish production monitoring mechanisms covering performance, risk, cost optimization, and operational resilience.
Reusable Assets & Engineering Standards:
- Build reusable AI accelerators, reference architectures, design patterns, and engineering blueprints.
- Define AI architecture standards, governance frameworks, and delivery methodologies across the Financial Services practice.
- Create technical documentation, architecture artifacts, and implementation playbooks.
- Mentor architects, engineers, and delivery teams in AI best practices and enterprise architecture principles.
Technology Strategy & Innovation:
- Evaluate emerging AI platforms, frameworks, and technologies for enterprise adoption.
- Work closely with strategic technology partners including cloud providers and AI platform vendors.
- Identify opportunities to leverage existing capabilities rather than custom-building solutions unnecessarily.
- Contribute to AI thought leadership, innovation initiatives, and practice development activities.
Your Skills:
Essential:
- 10+ years of experience designing, architecting, and delivering enterprise Data, Analytics, AI, or Machine Learning solutions.
- Proven experience deploying AI/ML solutions into production environments at enterprise scale.
- Strong hands-on architecture experience across: Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents / Agentic Architectures, MLOps and LLMOps.
- Expertise with enterprise data platforms such as Databricks, Snowflake, Azure Data Platform, AWS Data & AI Services, Google Cloud AI Platforms.
- Experience designing knowledge retrieval architectures including vector databases, semantic search, and metadata-driven architectures.
- Strong understanding of cloud architecture, microservices, APIs, and event-driven architectures.
- Experience establishing AI governance, model monitoring, evaluation frameworks, and observability practices.
- Demonstrated experience in Financial Services, Banking, Insurance, Capital Markets, or another highly regulated industry.
- Strong knowledge of enterprise security, data privacy, risk management, and regulatory controls.
- Experience leading architecture reviews, technical governance forums, and executive stakeholder engagements.
- Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
Desirable:
- Product engineering or AI platform product development experience.
- Experience with Agentic AI frameworks and Model Context Protocol (MCP).
- Knowledge of OpenTelemetry and observability solutions for AI workloads.
- Exposure to Responsible AI frameworks and AI governance regulations.
- Consulting and client-facing delivery experience within global organizations.
- Public speaking, thought leadership, blogging, or technical publication experience.
- Financial Services domain certifications or cloud architecture certifications.
We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Governments 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.
Make It Real (what does it mean for you): You'd be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce as a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained Mental Health Champions across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy. You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's learning for life mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more. You will be joining one of the World's Most Ethical Companies, as recognised by Ethisphere for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.
Why you should consider Capgemini: Growing clients' businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you'll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what's possible. It's why, together, we seek out opportunities that will transform the world's leading businesses, and it's how you'll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you'll build the skills you want. You'll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini: 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. With our strong heritage of nearly 60 years, we 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 our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of 22.1 billion.
Lead AI Architect - London employer: Capgemini
Capgemini is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a hybrid working model, employees enjoy the flexibility of blending office, client site, and home working, while also benefiting from extensive growth opportunities and professional development within the Capital Markets sector. Join us to be part of a team that values governance excellence and empowers you to make a meaningful impact in complex programme environments.
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We think this is how you could land Lead AI Architect - London
✨Join Local Tech Meetups
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We think you need these skills to ace Lead AI Architect - London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Capgemini.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Capgemini and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Capgemini
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Capgemini uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.