4 days ago
Manchester, United Kingdom +3 moreSenior
Responsibilities
- Serve as a senior or lead engineer on client AI platform engagements.
- Architect and deploy GPU-accelerated AI infrastructure, Kubernetes/OpenShift platforms, and cloud-native services across cloud, on-premises, and hybrid environments.
- Build and operate model-serving and gateway infrastructure, agent orchestration and tool-calling frameworks, evaluation harnesses, and guardrail and governance layers.
- Implement MLOps and LLMOps pipelines for model deployment, monitoring, retraining, and relevant fine-tuning using Infrastructure-as-Code, GitOps, and CI/CD.
- Establish AI-specific observability, security, governance, cost attribution, and lifecycle-management frameworks.
- Lead client workshops, architecture reviews, technical briefings, monitoring, troubleshooting, and operational support.
- Contribute to proposals, RFPs, bids, client pitches, offering development, internal projects, and practice culture.
- Coach and mentor colleagues while developing expertise in new technologies.
Requirements
- Active SC (Security Check) Clearance, or eligibility and willingness to obtain it, is required.
- Deep hands-on experience in most listed AI/GenAI platform engineering areas, including model serving, gateways, agent orchestration, evaluation engineering, guardrails, and AI observability.
- Experience with MLOps platforms such as Azure ML, Databricks, or SageMaker and vector or retrieval databases such as Pinecone, Milvus, or pgvector.
- Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks; fine-tuning, RLHF, or SLM distillation is a plus.
- Deep Kubernetes and container-platform expertise, including OpenShift, AKS, EKS, GKE, or VMware Tanzu.
- Experience with Terraform, Bicep, Ansible, GitOps, CI/CD pipelines, and DevOps processes in client-facing consulting environments.
- At least 5 years of experience across Azure, AWS, or GCP.
- Strong Python and one systems language such as Go or Rust, or Bash; experience with Git, GitHub, or GitLab.
- Ability to lead architecture reviews, workshops, and executive briefings and communicate with technical and non-technical stakeholders.
- Experience in financial services, insurance, or other regulated industries is preferred.
Benefits
- Hybrid working and flexible working arrangements are available to UK employees.
- Formal training and certifications are available across AWS, Azure, GCP, AI/ML, Scrum Master, Product Owner, and SAFe.
- Access to the Les Fontaines training environment near Paris, monthly showcases, team drinks, breakfasts, and away days.
- Wellbeing support includes Mental Health Champions and access to Thrive and Peppy wellbeing apps.
- The office base is London, Manchester, or Glasgow, with full flexibility required for assignments and possible periods away from home at short notice.
- The remuneration package includes flexible benefits and a variable performance-dependent element; no base salary amount is stated.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.