Lead AI Engineer

Lead AI Engineer Overview

This position is for a senior AI engineering professional who can take advanced machine learning and generative AI ideas and turn them into production-ready systems that operate reliably at enterprise scale. The role is centred on closing the gap between experimental prototypes and real business deployment, with a strong focus on building the right architecture, delivery practices, and safeguards so that AI solutions create measurable value in live environments.

You will be working on the design and delivery of end-to-end AI and machine learning systems, covering the full lifecycle from data preparation and model development through to deployment, feature management, monitoring, and ongoing operational control. A major part of the role is to help organisations adopt modern generative AI and agentic approaches in a practical way, using current frameworks and cloud services to build solutions that are scalable, dependable, and responsible.

What you will do

• Design and deliver complete AI/ML solutions from the earliest data preparation stages through to model build, deployment, feature store usage, model management, and monitoring.
• Build and apply solutions using current generative AI and agentic frameworks, including tools such as ADK, LangGraph, Microsoft Agent Framework, LlamaIndex, and similar technologies.
• Translate business AI opportunities into suitable data and AI architectures, choosing the most appropriate cloud services across major hyperscaler platforms.
• Lead teams made up of people from different disciplines to deliver complex work that spans business, data, and engineering concerns.
• Create and implement generative AI architectures, including retrieval-augmented generation pipelines, agent-based workflows, and orchestration for large language models across Azure, GCP, or AWS.
• Build in safety, evaluation, and assurance controls throughout the AI lifecycle so that solutions are ethical, explainable, and responsible by design.
• Work with product managers, data scientists, and business stakeholders to ensure the solutions delivered are aligned to business needs and generate real impact.
• Develop client-ready demonstrations and proof-of-value materials, contribute to proposals, and provide technical deep-dives that help shape and win work.
• Create reusable delivery assets and frameworks that can be used across multiple accounts and help accelerate future delivery.
• Contribute to internal capability building through thought leadership, blog writing, and accelerator development in areas such as agentic AI, LLM operations, and evaluation frameworks.

What the team is looking for

• Experience in a major consulting firm, or in an industry role where you have worked with a consulting-style mindset, including success in a matrixed organisation and the ability to gain commitment from peers when selling and delivering solutions.
• Experience collaborating with both technical and non-technical client sponsors to define requirements and shape solutions together.
• A strong record of designing and implementing MLOps strategies and frameworks, with evidence of delivering AI/ML solutions at scale from concept through to production.
• Deep knowledge of generative AI and agentic AI, including retrieval-augmented generation, embeddings, evaluation harnesses, and orchestration frameworks.
• Experience building cloud-native data and AI architectures using Azure, GCP, AWS, and/or Databricks.
• The ability to demonstrate how scaling AI can unlock business value and create meaningful impact.
• Hands-on experience deploying and scaling AI solutions on at least one major cloud platform, such as Azure, GCP, or AWS, using services like Azure Foundry, AI Studio, OpenAI, AKS, Vertex AI, Cloud Run, Bedrock, or SageMaker.
• Experience creating and automating AI/ML pipelines using 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 comparable tools.
• Ability to design and implement RAG pipelines, agentic workflows, MCP integrations, and connections to LLM APIs such as OpenAI, Anthropic, Hugging Face, or similar providers.
• Strong capability in CI/CD and containerisation, including GitHub Actions, Azure DevOps, Docker, and Kubernetes.
• Helpful additional knowledge includes AI evaluation techniques such as prompt testing, A/B testing, and quality assessment frameworks.
• It is also useful to understand modern data patterns such as lakehouse architectures, vector databases, and relational or NoSQL stores.
• Additional familiarity with API gateways, event streaming, and broader integration patterns would be an advantage.
• You must have lived in the UK for the last five years to be eligible to apply for this role.

Working environment and culture

The organisation describes itself as a team of ambitious technology-focused people who enjoy bringing the latest innovations into real client environments where the work has visible, practical impact. The role sits within the Data & AI professional community and is part of a business that works across both public and private sector clients.

The culture emphasises experimentation, curiosity, and a willingness to explore emerging technologies. The team is trusted to work with the newest models and agentic frameworks, and there is an expectation that people will be self-starting, adaptable, and eager to learn as the technology landscape changes quickly.

Capgemini also highlights its commitment to diversity and inclusion, saying that it actively works to create an environment where employees can bring their whole selves to work. The company says it aims to support positive work-life balance and has embedded flexible working into its approach.

Benefits and support

• A remuneration package that includes flexible benefits you can choose according to your personal circumstances.
• A variable compensation element linked to grade, company performance, and individual performance.
• Hybrid working as a standard part of the organisation’s approach, with flexible working arrangements available to all UK employees on request.
• Support for employee wellbeing, including trained Mental Health Champions across business areas.
• Access to wellbeing applications such as Thrive and Peppy.
• A workplace that has received recognition as one of the UK’s best places to work and has also been recognised among the world’s most ethical companies.
• A strong focus on social impact, including efforts to reduce the company’s carbon footprint and improve access to the digital world.

The role also notes that while there is an office base location, you must be fully flexible about assignment location because the work may involve periods away from home at short notice.

Applicants are expected to apply through the company’s recruitment process, with the page offering an online application route and the option to start the application using LinkedIn.

Degree Requirement: Not Specified

Visa Sponsorship May be