Capgemini
Lead AI Engineer Overview
| Company Name | Capgemini |
| Job Role | Lead AI Engineer |
| Qualifications | Not Specified |
| Category | IT Jobs |
| Job Type | Full Time |
| Location | London |
This position is for a senior AI engineering leader who can take advanced machine learning, generative AI, and agentic AI ideas from early-stage concepts through to robust, production-ready systems used at enterprise scale. The role is centred on closing the gap between experimentation and real business deployment, with a strong emphasis on building solutions that are dependable, governed, and capable of delivering measurable value.
What you will do
- Lead the design and delivery of complete AI and machine learning solutions, covering the full lifecycle from data preparation and model development through to deployment, feature store design, model management, and ongoing monitoring.
- Build and operationalise generative AI and agentic systems using current frameworks and patterns, including orchestration approaches, retrieval-augmented generation, and large language model integration.
- Turn business needs and use-case requirements into practical data and AI architectures, choosing suitable services across major cloud platforms.
- Guide and coordinate multi-disciplinary teams as they work through complex technical and delivery challenges.
- Architect responsible AI solutions that include safety, evaluation, and assurance controls so that outputs are ethical, explainable, and trustworthy.
- Work closely with product managers, data scientists, and business stakeholders to ensure the solutions delivered create real commercial impact.
- Produce client-ready demonstrations and proof-of-value materials, support proposals, and provide technical deep dives that help shape and win new work.
- Create reusable delivery components, frameworks, and internal assets that speed up delivery across accounts and strengthen the wider practice.
- Contribute to internal and external thought leadership through blogs, accelerator content, and knowledge sharing on topics such as agentic AI, LLM operations, and evaluation methods.
What you will bring
- Background in a large consulting firm, or in industry with a consulting-oriented mindset, together with the ability to succeed in a matrixed organisation and gain commitment from colleagues when selling and delivering solutions.
- Experience working with both technical and non-technical client sponsors to shape requirements collaboratively and develop solutions.
- Proven ability to design and implement MLOps strategies and frameworks, with a strong record of taking AI and machine learning solutions from concept into production at scale.
- Strong understanding of generative AI and agentic AI, including retrieval-augmented generation, embeddings, evaluation harnesses, and orchestration frameworks.
- Experience creating cloud-native data and AI architectures across Azure, Google Cloud, AWS, and/or Databricks.
- Ability to demonstrate how scaling AI can unlock business value and tangible impact.
Technical experience and skills
The team works with a broad range of technologies, and you do not need to know every tool listed. What matters most is a solid foundation, a good mix of relevant experience, and the curiosity and adaptability to learn new tools as projects require. The team values self-driven people who can move quickly and learn fast.
- Experience deploying and scaling AI solutions on at least one major cloud platform, such as Azure, Google Cloud, or AWS, using relevant services and products.
- Experience building and automating AI and machine learning pipelines with tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow, or Google ADK.
- Practical experience with generative and agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar tools.
- Ability to design and implement retrieval-augmented generation pipelines, agentic workflows, MCP integrations, and connections to LLM APIs such as OpenAI, Anthropic, Hugging Face, or equivalent services.
- Strong proficiency in CI/CD and containerisation tools, including GitHub Actions, Azure DevOps, Docker, and Kubernetes.
- Desirable experience in evaluating AI system performance, including prompt testing, A/B testing, and quality assessment methods.
- Helpful familiarity with modern data patterns such as lakehouse architectures, vector databases, and relational or NoSQL stores.
- Useful knowledge of API gateways, event streaming, and general integration approaches.
Eligibility
To apply, you must have lived in the UK for the previous five years.
About the organisation and team environment
You would be joining a team of ambitious technology specialists who enjoy taking the newest tools and models into real client environments and seeing their work make a practical difference. The work spans both public and private sector clients, with a strong focus on innovation, delivery, and real-world impact rather than experimentation alone.
The organisation describes itself as fast-moving and highly engaged with emerging technology, with teams encouraged to explore new ideas and build with the latest models and agentic frameworks. There is also an emphasis on curiosity, initiative, and a self-starting approach.
Working environment, culture, and support
The company places strong emphasis on diversity, inclusion, and creating an environment where people can bring their whole selves to work. Flexible working is part of the culture, and hybrid working is embedded in the way the business operates. UK employees can request flexible working arrangements.
Employee wellbeing is treated as important, with trained Mental Health Champions available across business areas and access to wellbeing applications such as Thrive and Peppy. The organisation also highlights its commitment to social impact, including efforts to reduce its own carbon footprint and improve access to the digital world.
The employer has also received external recognition, including being named a Glassdoor Best Place to Work in the UK for two consecutive years and being recognised by the Ethisphere Institute as one of the world’s most ethical companies for the tenth time.
Additional working expectations
Although there is an office base location, you must be fully flexible about assignment location because the role may require periods away from home at short notice.
Pay and other details
The package includes flexible benefits and a variable pay component that depends on grade as well as company and personal performance.
Reference code: 404560. The role was posted on 25 August 2026. It is a permanent position at experienced professional level within the Data & AI community, and the listed locations are London, Newcastle upon Tyne, Birmingham, and Bristol.
How to apply
Applications can be started through the employer’s online application process, and the page also offers the option to begin applying with LinkedIn.
Degree Requirement: Not Specified
Visa Sponsorship May be
To apply for this job please visit careers.capgemini.com.
