MLOps Engineer; SC Clearance

Position Description

At CGI, you will play a pivotal role in enabling the deployment and operation of advanced AI systems that support critical national security outcomes. Working within our Space, Defence and Intelligence business unit, you will help design and deliver secure, scalable machine learning platforms that power innovation across mission‑critical environments.

Our Space, Defence and Intelligence business unit is an IT systems integrator that builds, operates and supports technically complex, mission‑critical systems for clients that need to keep operation safe and secure. We combine deep sector expertise with emerging technologies and agile delivery to create impactful solutions.

Due to the secure nature of the programme, you will need to hold UK Security Clearance or be eligible to undergo clearance. This position will be based on site near Gloucester five days a week.

In this role you will design, build and operate secure AI and machine learning platforms within highly controlled environments. You will develop the infrastructure and automation required to deploy, monitor and scale models in production, including large language models and other advanced AI systems. Working closely with multidisciplinary teams, you will deliver resilient, high‑performance platforms that enable critical decision‑making and operational effectiveness.

• Design & deliver secure, scalable MLOps platforms for production environments
• Build & optimise air‑gapped machine learning pipelines and workflows
• Deploy & manage LLM inference clusters and AI model hosting platforms
• Implement & enhance model lifecycle processes, including monitoring and retraining
• Develop & automate infrastructure using Dev Sec Ops  principles and tooling
• Monitor & improve system performance using observability tools and best practices
• Collaborate & innovate with cross‑functional teams to deliver mission‑critical solutions

• Experience building and operating production‑grade machine learning platforms
• Proficiency in Python for data or platform engineering
• Strong command‑line skills in Linux systems
• Experience with MLOps tools such as MLflow, Kubeflow or Airflow
• Familiarity with monitoring tools such as Prometheus or Grafana
• Experience with containerisation and orchestration (Docker, Kubernetes, Terraform)
• Understanding of CI/CD pipelines and Dev Sec Ops  practices
• Experience with platforms such as VMware, Open Shift or Open Stack (desirable)
• Exposure to AI/ML workloads, GPU environments, or secure/air‑gapped systems (advantageous)

• Competitive salary
• Excellent pension scheme
• Private healthcare
• Share scheme (3.5% + 3.5% matching)