DCI Job Requirement for:

AI Platform Engineer

Locations: McLean, VA

Job Description

Serves as an AI Platform Customer Service Manager and ML Engineer

Support customers leveraging next-gen infrastructure to drive innovation in AI field

Ensure customers achieve desired outcomes with our AI-powered solutions, by:

• Providing strategic guidance
• Technical support
• Relationship management

Identify and address potential customer pain points

Help customers maximize AI product value and achieve measurable success

Work closely with stakeholders from engineering, sales, and program management

Develop long-term relationships with customers

Use information to develop targeted strategies for customer success

Manage changes effectively and communicate with customers about updates

Optimize resource utilization, and implement best practices for cluster tuning.

Provide hands-on support with the following:

• Containerization & Orchestration
• Networking
• Security
• Performance and Optimization management
• CI/CD tooling
• Pipeline Design & Implementation
• Infrastructure as Code (IaC)

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 and Kustomize for Kubernetes application packaging and deployment.

Strong scripting skills in languages like Python, Go, Bash, or similar, for automating tasks, creating custom tooling, and integrating various systems

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

Clearance: Active TS/SCI with CI Polygraph

Job Type: Full-time

Pay: $200,000.00 - $250,000.00 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 and deploying Kubernetes clusters: 8 years (Preferred)
• Kubernetes networking concepts: 5 years (Preferred)
• CI/CD : 5 years (Preferred)
• Terraform, Pulumi, and/or CloudFormation : 5 years (Preferred)
• Python, Go, and/or Bash: 5 years (Preferred)

License/Certification:

• CI Polygraph Security Clearance (Preferred)

Security clearance:

• Top Secret (Required)

Work Location: In person