A
AI Platform Engineer / DevOps
Apolis
- 🇺🇸 United States
- On-site
- Senior
- 19 hours ago
- $60 – $62 / hour
- AI
- Devops
- AI/ML
- Machine Learning
- CI/CD
- MLOps
- GCP
- IaC
- Terraform
- Docker
- Kubernetes
- GKE
- Prometheus
- Grafana
- IAM
- Secrets Management
- Vertex AI
- Cloud Run
- VPC
- BigQuery
- Jenkins
- GitHub Actions
- GitLab CI
- ArgoCD
- Python
- Bash
- Gemini
- GitOps
- FinOps
- MLflow
- Kubeflow
19 hours ago
AI Platform Engineer / DevOps
Location: Charlotte, NC – Hybrid
About the Role
We are seeking a seniorAI Platform Engineer / DevOps Engineer to build, operate, and scale the infrastructure and tooling that power AI/ML and Generative AI workloads. This role focuses oncloud platform engineering, CI/CD automation, and MLOps practices that enable reliable, secure, and scalable delivery of AI systems.
Key Responsibilities
- Design, build, and maintain scalableGCP cloud infrastructure supporting AI/ML and application workloads.
- Architect and manageCI/CD pipelines for model training, deployment, and application release workflows.
- Build and maintainMLOps pipelines for model versioning, training, deployment, and monitoring.
- ImplementInfrastructure as Code (IaC) using Terraform and/or Deployment Manager.
- Containerize and orchestrate services usingDocker and Kubernetes/GKE.
- Establish observability, logging, and alerting for AI/ML services usingCloud 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.
- Implement platform security,IAM policies, secrets management, and compliance across environments.
- Drive automation to reduce manual effort across build, testing, deployment, and rollback processes.
- Troubleshoot infrastructure and platform issues and performroot-cause analysis for production incidents.
Required Qualifications
- 7+ years of experience in Platform Engineering, DevOps, Infrastructure Engineering, or related roles.
- Strong hands-on experience withGoogle Cloud Platform (GCP), including:
- Vertex AI
- GKE
- Cloud Run
- IAM
- VPC / Networking
- BigQuery
- Strong experience designing and managingCI/CD pipelines using technologies such as:
- Cloud Build
- Jenkins
- GitHub Actions
- GitLab CI
- ArgoCD
- Strong proficiency withInfrastructure as Code, preferably Terraform.
- Strong scripting/programming skills usingPython, Bash, or Go.
- Hands-on experience withDocker and Kubernetes.
- Solid understanding ofMLOps and the ML lifecycle, including training, model versioning, deployment, and monitoring.
- Experience with observability tools such as:
- Cloud Monitoring
- Prometheus
- Grafana
- ELK/EFK
- Strong understanding ofcloud 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 supportingGenerative AI / LLM platforms, including Vertex AI, Gemini Enterprise, or Model Garden.
- Experience withGitOps workflows using ArgoCD or Flux.
- Experience working inregulated or enterprise-scale environments.
- Familiarity withGCP cost optimization and FinOps practices.
Key Skills
GCP | Vertex AI | GKE | Cloud Run | BigQuery | Kubernetes | Docker | Terraform | CI/CD | Cloud Build | Jenkins | GitHub Actions | ArgoCD | MLOps | MLflow | Kubeflow | Python | Bash | Go | IAM | VPC | Prometheus | Grafana | Cloud Monitoring | Cloud Logging | ELK/EFK | Generative AI | LLM | GitOps
Top 3 Must-Have Skills
- GCP / Vertex AI / GKE
- CI/CD + Terraform + Kubernetes
- MLOps / AI-ML Platform Engineering
AI Platform Engineer / DevOps · Apolis