Contract Cloud Platform Engineer for AI/ML & MLOps

Capgemini; Charlotte (NC); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Retirement benefits

Job summary

Capgemini seeks an experienced platform engineer to build and scale AI platform infrastructure in Charlotte, NC. You will design scalable GCP cloud infrastructure for AI/ML workloads and manage CI/CD pipelines and MLOps pipelines across the ML lifecycle.

You will containerize services with Docker/Kubernetes, implement IaC with Terraform, and ensure security and observability. This is an onsite contract role with Capgemini, partnering with AI/ML teams to productionize models.

Qualifications

• 7+ years of experience in platform engineering, DevOps, or infrastructure engineering.
• Hands-on expertise in Google Cloud Platform (GCP) including Vertex AI, GKE, Cloud Run, IAM, VPC/networking, and BigQuery.
• Deep experience designing and managing CI/CD pipelines (Cloud Build, Jenkins, GitHub Actions, GitLab CI, ArgoCD).
• Proficiency with Infrastructure as Code (Terraform preferred).
• Strong scripting/programming in Python, Bash, or Go.
• Experience with containers and orchestration (Docker, Kubernetes).
• Familiarity with MLOps across ML lifecycle: training, versioning, deployment, monitoring.
• Observability tooling such as Cloud Monitoring, Prometheus, Grafana, ELK/EFK.
• Cloud security, IAM, and secrets management best practices.

Responsibilities

• Design, build, and maintain scalable GCP cloud infrastructure for AI/ML and application workloads.
• Architect and manage CI/CD pipelines for model training, deployment, and application release workflows.
• Create and run MLOps pipelines for model versioning, training, deployment, and monitoring.
• Use Infrastructure as Code for repeatable, auditable environment provisioning.
• Containerize and orchestrate services with Docker and Kubernetes (GKE).
• Set up observability including logging and alerting for AI/ML services.
• Partner with AI/ML engineers and data scientists to productionize models.
• Implement platform security with IAM, secrets management, and compliance.
• Drive automation to reduce manual toil across build, test, deployment, rollback workflows.
• Troubleshoot platform and infrastructure issues and lead root-cause resolution.

Skills

Cloud platform engineering

DevOps

CI/CD pipelines

MLOps

Scripting (Python/Bash/Go)

Security and IAM

Tools

GCP

Vertex AI

GKE

Cloud Run

Terraform

Deployment Manager

Docker

Kubernetes

GitHub Actions

Jenkins

GitLab CI

ArgoCD

Kubeflow

MLflow

Prometheus

Grafana

Cloud Monitoring/Cloud Logging

ELK/EFK

Job description

Capgemini seeks an experienced platform engineer to build and scale AI platform infrastructure in Charlotte, NC. You will design scalable GCP cloud infrastructure for AI/ML workloads and manage CI/CD pipelines and MLOps pipelines across the ML lifecycle.

You will containerize services with Docker/Kubernetes, implement IaC with Terraform, and ensure security and observability. This is an onsite contract role with Capgemini, partnering with AI/ML teams to productionize models.