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Lead AI Engineer
Lead AI Engineer
About the Role
We’re seeking a Lead AI Engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. This role bridges AI prototypes with practical business solutions, ensuring AI moves responsibly and reliably from lab to live.
As a key player, you’ll:
- Design and deliver end-to-end AI/ML systems, covering data preparation, model development, deployment, feature stores, model management, and monitoring.
- Pioneer Generative AI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex, and CrewAI, embedding advanced RAG pipelines and orchestration across Azure, GCP, or AWS.
- Translate AI use cases into cloud-native data and AI architectures, leveraging hyperscaler services.
- Lead multi-disciplinary teams in executing complex projects.
- Embed safety, evaluation, and assurance mechanisms, ensuring ethical, explainable, and scale-ready solutions.
- Collaborate with Product Managers, Data Scientists, and stakeholders to drive business value and impact.
Core Growth Opportunities
You’ll also contribute to:
- Business Development – Build demos/POVs, support proposals, and showcase delivery patterns.
- Internal Contribution – Develop reusable assets, frameworks, and best practices.
- Capability Development – Contribute to thought leadership (e.g., Agentic AI, LLMOps, or evaluation frameworks).
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Requirements
What You’ll Bring
We’re looking for candidates with:
- Consulting or industry experience, adaptable to a matrixed organisation, with a track record of selling and delivering solutions cross-functionally.
- Proven expertise in MLDevOps—designing MLOps strategies/models at scale from concept to production.
- Expertise in Generative AI and Agentic AI, with hands-on experience in RAG pipelines, embeddings, and orchestration.
- Ability to measure AI’s business impact and demonstrate scalable value creation.
- Cloud-native architecture design with Azure, GCP, AWS, or Databricks.
Technical Profile
Essential Skills
A solid foundation in:
- Cloud Platform Deployment & Scaling: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker).
- AI/ML Pipeline Automation: MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow, or Google ADK.
- Generative & Agentic AI: Hands-on experience with LangChain, LlamaIndex, CrewAI, Autogen, or similar frameworks.
- RAG Pipelines & Agentic Workflows: Integration with LLM APIs (OpenAI, Anthropic, Hugging Face).
- CI/CD & Containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes.
Nice-to-Haves
Additional strength in:
- AI System Evaluation: Prompt engineering, A/B testing, quality frameworks.
- Modern Data Patterns: Lakehouse architectures, vector databases, relational/NoSQL stores.
- Integration Patterns: API gateways, event streaming.
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Eligibility
- Must have resided in the UK for the last 5 years.
About Capgemini
Why Join Us?
We’re a team of innovators who leverage cutting-edge tech to deliver tangible real-world impact in both public and private sectors. Our culture thrives on:
- Proactive exploration of new technologies and frameworks.
- Innovation cycles that lead to adoptable, production-grade solutions.
Why It Matters
We’re proud to be: ✅ Ranked “Best UK Workplaces” on Glassdoor for 2 consecutive years. ✅ Ethics leaders (named by Ethisphere Institute for the 10th year). ✅ Dedicated to purpose-driven tech, reducing carbon footprints and advancing digital inclusion.
WorkLife Flexibility
We advocate for a positive work-life balance: 🔹 Hybrid & flexible working as standard for UK employees. 🔹 Tabled wellbeing programs (Thrive, Peppy, Mental Health Champions). 🔹 Location flexibility—roles may require temporary travel assignments.
Compensation & Benefits
✨ Competitive remuneration packages, performance-based variable incentives. ✨ Bespoke benefits aligned with employee needs.
There’s no better place to build the future of AI than Capgemini. Apply if you’re ready to push boundaries.
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