AI Platform Engineer

AI Platform Engineer

Location: Charlotte, NC – Onsite Experience: 7+ Years

Job Overview

We are seeking a Senior AI Platform Engineer to build, operate, and scale the infrastructure and tooling that power AI/ML and Generative AI workloads. The role focuses on cloud platform engineering, CI/CD automation, MLOps, security, observability, and reliable production delivery of AI systems.

Key Responsibilities

• Design, build, and maintain scalable GCP cloud infrastructure supporting AI/ML and application workloads.
• Architect and manage CI/CD pipelines for model training, deployment, and application release workflows.
• Build and maintain MLOps pipelines for model versioning, training, deployment, and monitoring.
• Implement Infrastructure as Code using Terraform and Deployment Manager.
• Containerize and orchestrate services using Docker and Kubernetes/GKE.
• Establish observability, logging, and alerting for AI/ML services using Cloud Monitoring, Cloud Logging, Prometheus, and Grafana.
• Partner with AI/ML engineers and data scientists to productionize models and streamline the path from experimentation to production.
• Ensure platform security through IAM policies, secrets management, and compliance controls.
• Drive automation across build, test, deployment, and rollback processes.
• Troubleshoot platform and infrastructure issues and perform root-cause analysis for production incidents.

Required Qualifications

• 7+ years of experience in Platform Engineering, DevOps, Infrastructure Engineering, or related roles.
• Strong hands-on expertise with Google Cloud Platform (GCP), including: Vertex AI, GKE, Cloud Run, IAM, VPC / Networking, BigQuery.
• Deep experience designing and managing CI/CD pipelines using: Cloud Build, Jenkins, GitHub Actions, GitLab CI, ArgoCD.
• Strong proficiency in Infrastructure as Code, preferably Terraform.
• Strong scripting/programming skills using Python, Bash, or Go.
• Experience with Docker and Kubernetes.
• Strong understanding of MLOps and the ML lifecycle, including: Training, Versioning, Deployment, Monitoring.
• Experience with observability tools such as: Cloud Monitoring, Prometheus, Grafana, ELK / EFK.
• Strong understanding of cloud security, IAM, and secrets management best practices.

Preferred Qualifications

• GCP Professional certifications such as: Professional Cloud DevOps Engineer, Professional Cloud Architect, Professional Machine Learning Engineer.
• Experience supporting Generative AI / LLM platforms, including: Vertex AI, Gemini Enterprise, Model Garden.
• Experience with GitOps workflows using ArgoCD or Flux.
• Experience working in regulated or enterprise-scale environments.
• Familiarity with GCP cost optimization and FinOps practices.

Core Skills

GCP | Vertex AI | GKE | Cloud Run | BigQuery | IAM | VPC/Networking | Terraform | Docker | Kubernetes | CI/CD | Cloud Build | Jenkins | GitHub Actions | GitLab CI | ArgoCD | MLOps | Kubeflow | MLflow | Python | Bash | Go | Prometheus | Grafana | ELK/EFK | Cloud Monitoring | Cloud Logging | Generative AI | LLM | Gemini Enterprise | Model Garden | GitOps | Cloud Security | Secrets Management | FinOps