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Capgemini

Global consulting, technology services, outsourcing

AI Platform Engineer Senior Consultant - AI and Digital Factory

Platform EngineeringUpdated on Nov 14
Full-timeNo salary listed

About the Job

Requirements

  • Hold active Security Check clearance or be eligible and willing to obtain it.
  • Have deep hands-on experience in most of the listed areas, with strong depth in AI and generative AI platform engineering.
  • Have experience with model serving and gateway infrastructure, including routing, failover, and per-workload cost attribution.
  • Have familiarity with agent orchestration and tool-calling frameworks, including the Model Context Protocol.
  • Have experience with evaluation engineering, including golden datasets, regression gates in continuous integration, and large language model judge calibration.
  • Have experience with guardrail and AI observability tooling.
  • Have hands-on experience with MLOps platforms and vector or retrieval databases.
  • Have experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks.
  • Have deep expertise in Kubernetes and container platforms.
  • Have experience with infrastructure as code and DevOps practices, including Terraform, Bicep, Ansible, GitOps, and continuous integration and continuous delivery pipelines.
  • Have at least five years of experience across Azure, AWS, or Google Cloud Platform, with strong DevOps fundamentals.
  • Have proven experience in DevOps processes and best practices in a client-facing consulting context.
  • Be able to lead architecture reviews, workshops, and executive briefings.
  • Have the time and risk management, problem-solving, and empathetic leadership skills needed for consulting.
  • Be able to communicate appropriately with internal and external stakeholders.
  • Have strong scripting ability in Python and one systems language such as Go or Rust, or Bash.
  • Have experience using version control software such as Git, GitHub, or GitLab.

Responsibilities

  • Serve as a senior or lead engineer on client AI platform engagements.
  • Architect and deploy AI-ready infrastructure, including GPU-accelerated compute, Kubernetes or OpenShift, and cloud-native services, across cloud, on-premises, and hybrid environments.
  • Build and operate core AI platform components, including 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 continuous integration and continuous delivery.
  • Establish observability, security, and governance frameworks specific to AI systems, including cost attribution and lifecycle management.
  • Work with clients and internal teams to develop opportunities and build an AI platform engineering culture.
  • Lead client workshops, architecture reviews, and technical briefings; provide operational support, including monitoring and troubleshooting.
  • Share knowledge and experience with colleagues by coaching and mentoring them, while continuing to develop skills through experimentation and learning new technologies.
  • Help shape the AI Platform Engineering offering.
  • Lead or contribute to proposals, requests for proposals, bids, proposition development, client pitches, and client hosting at events.
  • Contribute to internal projects, campaign development, think tanks, whitepapers, practice development, and offering development.
  • Participate in training and certifications that support career development and company skills needs.

Desired Qualifications

  • Exposure to fine-tuning, reinforcement learning from human feedback, or small language model distillation.
  • Experience in financial services, insurance, or another regulated industry.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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