AI Platform Engineer

Serves as an AI Platform Engineer

Provide Technical Cluster Management:

• Design, deploy, secure, maintain, and upgrade scalable Kubernetes clusters
• Understand control plane components, worker nodes, and their interactions

Provide Containerization & Orchestration support

Secure Kubernetes environments

Diagnose and resolve complex performance issues within Kubernetes

Optimize resource utilization, and implement best practices for cluster tuning

Troubleshooting issues across the entire Kubernetes stack

Design, implement, and maintain robust, automated CI/CD pipelines for:

• Deploying containerized applications to Kubernetes

Provision and manage infrastructure declaratively

Use languages like Python, Go, Bash, or similar, to automating tasks

BS in Computer Science / Engineering (or related career field)

Extensive experience designing, deploying, securing, maintaining, and upgrading:

• Highly available, scalable Kubernetes clusters
• Ex. EKS, AKS, GKE, OpenShift, or self-managed)

Understanding of control plane components, worker nodes, and their interactions

Proficient with Docker and containerization best practices

Advanced knowledge of Kubernetes primitives like:

• Pods, Deployments, StatefulSets, Services, Ingress, ConfigMaps
• Secrets, Persistent Volumes, and Namespaces

Strong understanding of Kubernetes networking concepts, policies, meshes

• Along with DNS within and outside the cluster

Expertise in securing Kubernetes environments, including:

• RBAC and Pod Security Policies/Admission Controllers
• Vulnerability scanning, secret management
• Network security

Ability to diagnose and resolve complex performance issues within Kubernetes

Experience IDing and resolving issues across Kubernetes stack

Hands-on experience with popular CI/CD platforms like:

• Jenkins, GitLab CI/CD, GitHub Actions, Tekton, Argo Workflows, etc.

Ability to design, implement, and maintain robust, automated CI/CD pipelines

• For deploying containerized applications to Kubernetes,

Proficiency with IaC tools such as Terraform, Pulumi, or CloudFormation

Experience with Helm charts for Kubernetes packaging and deployment

Strong scripting skills in languages like:

• Python, Go, Bash, or similar

Practical experience with GitOps workflows and tools

Experience with Prometheus, Grafana, ELK stack/OpenSearch, Datadog, Splunk

AWS Certified DevOps Engineer

Azure DevOps Engineer

Have current IAM Level II to satisfy DOD 8570 IAT requirements

Ability to travel up to 20% of the time, as required, to Clearance Requirements

Clearance: Active TS/SCI with CI Polygraph, * designing, deploying, maintaining Kubernetes clusters: 5 years (Preferred)

• Kubernetes primitives : 5 years (Preferred)
• securing Kubernetes environments: 5 years (Preferred)
• designing, implementing maintaining CI/CD pipelines : 5 years (Preferred)
• Python and/or Go programming : 5 years (Preferred)
• Docker and containerization : 5 years (Preferred)

License/Certification:

• CI Polygraph Security Clearance (Preferred)

Professional development assistance, Tuition reimbursement, Parental leave, 401(k), Health insurance, Retirement plan, 401(k) matching, Paid time off Full-time Chantilly, VA 20153, Salary: $220,000-$270,000

Pay: $220,000.00 - $270,000.00 per year, * 401(k)

• 401(k) matching
• Dental insurance
• Employee assistance program
• Flexible schedule
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Parental leave
• Professional development assistance
• Relocation assistance
• Retirement plan
• Tuition reimbursement
• Vision insurance