Job Type: Full-time
DCI Job Requirement for:
AI Platform Engineer
Locations: Chantilly, VA
Job Description
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
Qualifications:
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
Salary: $220,000-$270,000
Pay: $220,000.00 - $270,000.00 per year
Benefits:
- 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
Experience:
- 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)
Security clearance:
Work Location: In person
