About the Role
At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Our AI Platform Engineering Senior Consultants sit within AI & Digital Factory, part of the Business Technology practice in Capgemini Invent, which leads digital transformation projects across Capgemini.
Responsibilities
•Be a senior or lead engineer on client AI platform engagements
•Architect and deploy AI-ready infrastructure (GPU-accelerated compute, Kubernetes/OpenShift, and cloud-native services) across cloud, on-premises, and hybrid environments
•Build and operate core AI platform components: model serving and gateway infrastructure, agent orchestration and tool-calling frameworks, evaluation harnesses, and guardrail/governance layers
•Implement MLOps and LLMOps pipelines (model deployment, monitoring, retraining, and fine-tuning where relevant) using Infrastructure-as-Code, GitOps, and CI/CD
•Establish observability, security, and governance frameworks specific to AI systems, including cost attribution and lifecycle management
•Work with clients and internal teams to develop new opportunities and shape a strong AI platform engineering culture
•Lead client workshops, architecture reviews, and technical briefings; provide operational support including monitoring and troubleshooting
•Share your knowledge and experience with colleagues as you coach and mentor them, while developing your own skills by experimenting with and learning new technologies
•People/line manager, stakeholder management and communication, recruitment, etc.
•Help to shape the AI Platform Engineering offering
•Leading/contributing to proposals, RFPs, bids, proposition development, client pitch contribution, client hosting at events
•Internal projects, campaign development, internal think-tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development
•Training to support your career development and the skills demand within the company, certifications etc.
Requirements
To be considered for this position you must hold active SC (Security Check) Clearance, or be eligible and willing to gain this level of clearance. You'll bring deep, hands-on experience in most of the areas below, with strong depth in AI/GenAI platform engineering specifically. You don't need to tick every box.
•Model serving and gateway infrastructure (e.g. vLLM, LiteLLM, managed endpoints), with routing, failover, and per-workload cost attribution
•Agent orchestration and tool-calling frameworks (e.g. LangGraph or equivalent), including familiarity with the Model Context Protocol (MCP)
•Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration)
•Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)
•Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)
•Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks
•Deep expertise in Kubernetes and container platforms (OpenShift, AKS, EKS, GKE, or VMware Tanzu)
•Infrastructure as Code and DevOps practices (Terraform, Bicep, Ansible, GitOps and CI/CD pipelines)
•5+ years' experience across Azure, AWS, or GCP; strong DevOps fundamentals
•Proven experience in DevOps processes and best practices, applied in a client-facing consulting context
•Ability to lead architecture reviews, workshops, and executive briefings
•Strong soft skills key to consulting: time and risk management, problem solving, leading with empathy
•Ability to converse with both internal and external stakeholders, always holding the appropriate level of conversation
•Strong scripting ability (Python plus one systems language such as Go or Rust, or Bash)
•Experience using version control software (Git, GitHub, GitLab)
Nice to Have
•Exposure to fine-tuning, RLHF, or SLM distillation is a strong plus
•Experience with financial services, insurance, or other regulated-industry engineering is a strong plus, given the compliance demands of AI in these sectors
Conditions
•You'll gain exposure to high-profile transformations and hands-on exposure to leading AI technologies
•Formal training by industry experts, with access to certifications across cloud (AWS, Azure, GCP), AI/ML, and Agile delivery (Scrum Master, Product Owner, SAFe)
•Les Fontaines — our unique training environment just outside of Paris, for thought-leadership and capability building
•Monthly showcases of our digital transformation initiatives, plus monthly team drinks, breakfasts, and away days
•We aim to build an environment where employees can enjoy a positive work-life balance. We embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements
•Employee wellbeing is vitally important to us as an organisation. We have trained 'Mental Health Champions' across each of our business areas, and have invested in wellbeing apps such as Thrive and Peppy
•Whilst you will have London, Manchester or Glasgow as an office base location, you must be fully flexible in terms of assignment location, as these roles may involve periods of time away from home at short notice
•We offer a remuneration package which includes flexible benefits options for you to choose to suit your own personal circumstances and a variable element dependent on grade and on company and personal performance
