AI Platform Engineer- Senior Consultant-AI and Digital Factory

AI Platform Engineer- Senior Consultant-AI and Digital Factory

Full-Time 63000 - 77000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Design and build AI platforms that power innovative solutions for clients.
  • Company: Join Capgemini Invent, a leader in digital transformation and innovation.
  • Benefits: Enjoy flexible working, competitive salary, and access to top-notch training.
  • Other info: Be part of a diverse team focused on personal growth and social impact.
  • Why this job: Make a real impact with cutting-edge AI technologies and drive meaningful change.
  • Qualifications: Experience in AI platform engineering and strong collaboration skills required.

The predicted salary is between 63000 - 77000 £ per year.

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. Join us to drive transformation tailored to our client’s challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.

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. We are a dynamic community that values innovation, professional development, and the ability to make a real difference for our clients.

As an AI Platform Engineer, you’ll design, build, and operate the infrastructure that enterprise AI and Generative AI workloads run on: the platform layer beneath LLMs, agents, and MLOps pipelines. This spans GPU-accelerated compute and container platforms, model serving and gateway infrastructure, evaluation and guardrail systems, and the MLOps/LLMOps tooling that takes a model from experiment to production. You’ll work across hybrid and multi-cloud environments, helping clients modernize their AI infrastructure and adopt AI safely and at scale.

As part of your role, you will:

  • 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

As part of your role you will also have the opportunity to contribute to the business and your own personal growth, through activities that form part of the following categories:

  • Leadership: People/line manager, stakeholder management and communication, recruitment, etc. Help to shape the AI Platform Engineering offering.
  • Business Development: Leading/contributing to proposals, RFPs, bids, proposition development, client pitch contribution, client hosting at events.
  • Internal contribution: Internal projects, campaign development, internal think-tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development.
  • Learning & development: Training to support your career development and the skills demand within the company, certifications etc.

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.

  • AI & GenAI Platform Engineering: 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)
  • MLOps & LLMOps: 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; Exposure to fine-tuning, RLHF, or SLM distillation is a strong plus
  • Cloud-Native & Infrastructure: 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
  • Consulting & Delivery: 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
  • General: Strong scripting ability (Python plus one systems language such as Go or Rust, or Bash); Experience with financial services, insurance, or other regulated-industry engineering is a strong plus, given the compliance demands of AI in these sectors; Experience using version control software (Git, GitHub, GitLab)

We are delighted to have received the ‘Glassdoor Best Places to work in the UK’ accolade for 4 consecutive years. Capgemini Invent offers Consultants a culture of learning, ownership, and focus on value.

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.

At Capgemini we don’t just believe in Diversity & Inclusion, we actively go out to making it a working reality. Driven by our core values and Active Inclusion Campaign, we build environments where you can bring your whole self to work. 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.

Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role. Please opt in during the application process.

We’re also focused on using tech to have a positive social impact — working to reduce our own carbon footprint and improve everyone’s access to a digital world. We were named one of the world’s most ethical companies by the Ethisphere Institute for the 10th year. When you join Capgemini, you’ll join a team that does the right thing.

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.

AI Platform Engineer- Senior Consultant-AI and Digital Factory employer: Capgemini

Capgemini is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a hybrid working model, employees enjoy the flexibility of blending office, client site, and home working, while also benefiting from extensive growth opportunities and professional development within the Capital Markets sector. Join us to be part of a team that values governance excellence and empowers you to make a meaningful impact in complex programme environments.

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Contact Details:

Capgemini Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Platform Engineer- Senior Consultant-AI and Digital Factory

✨Join Local Tech Meetups

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✨Contribute to Open Source Projects

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We think you need these skills to ace AI Platform Engineer- Senior Consultant-AI and Digital Factory

AI Platform Engineering
Model Serving Infrastructure
Agent Orchestration Frameworks
MLOps and LLMOps Implementation
Kubernetes and Container Platforms
Infrastructure as Code
DevOps Practices

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Capgemini.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Capgemini and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Capgemini

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Capgemini uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.