AI Engineer

Capgemini is seeking a Senior AI Platform Engineer for a contract role based in Charlotte, NC (onsite). This position will focus on building, operating, and scaling infrastructure and tooling for AI/ML and generative AI workloads, with an emphasis on cloud platform engineering and dependable delivery.

You will help create repeatable pipelines and production-ready environments across the full MLOps lifecycle, partnering with AI/ML engineers and data scientists to streamline the path from experimentation to reliable deployment.

Role focus

• Build and maintain scalable cloud infrastructure on Google Cloud Platform (GCP) to support AI/ML and application workloads
• Architect and manage CI/CD pipelines for model training, deployment, and application release workflows
• Develop MLOps pipelines for model versioning, training, deployment, and monitoring
• Use Infrastructure as Code to provision environments that are repeatable and auditable
• Containerize and orchestrate services using Docker and Kubernetes (GKE)

Key responsibilities

• Establish observability, logging, and alerting for AI/ML services using Cloud Monitoring, Cloud Logging, and Prometheus/Grafana
• Implement platform security across environments, including IAM policies, secrets management, and compliance
• Drive automation to reduce manual toil across build, test, deployment, and rollback workflows
• Troubleshoot platform and infrastructure issues and drive root-cause resolution for production incidents
• Partner with AI/ML engineers and data scientists to productionize models and streamline experimentation-to-production workflows

Required skills and experience

• 7+ years of experience in platform engineering, DevOps, or infrastructure engineering
• Hands-on expertise with GCP, including Vertex AI, GKE, Cloud Run, IAM, VPC/networking, and BigQuery
• Deep experience designing and managing CI/CD pipelines using tools such as Cloud Build, Jenkins, GitHub Actions, GitLab CI, or ArgoCD
• Proficiency with Infrastructure as Code, with Terraform preferred
• Strong scripting/programming skills in Python, Bash, or Go
• Experience with containerization and orchestration using Docker and Kubernetes
• Solid understanding of MLOps concepts and the ML lifecycle, including training, versioning, deployment, and monitoring
• Experience with observability tooling such as Prometheus, Grafana, and ELK/EFK
• Strong understanding of cloud security, IAM, and secrets management best practices

Technologies

GCP, Google Cloud Platform, Vertex AI, GKE, Cloud Run, IAM, VPC/networking, BigQuery, Cloud Build, GitHub Actions, Jenkins, GitLab CI, Vertex AI Pipelines, Kubeflow, MLflow, Terraform, Deployment Manager, Docker, Kubernetes, Prometheus, Grafana, Cloud Monitoring, Cloud Logging, Python, Bash, Go, ELK/EFK, ArgoCD

Benefits

• Medical, dental, vision, and retirement benefits

Compensation: USD 36 - 57 per hour
Job type: contract
Experience level: 7+ years