Platform Engineering Architect — AI & Secure DevSecOps

Clarityinnovates; Jessup (MD); On-site; USD 225,000 - 375,000; Full time

Job summary

Clarity Innovations, a government-focused technology partner, is seeking a Platform Engineering Architect to advance AI capabilities across the enterprise stack.

You will own the AI access platform on Kubernetes, deploy AI services, integrate frontier models, and shape MLOps pipelines while ensuring security and governance in national security contexts. This role demands deep Kubernetes, CI/CD, and cloud expertise in a fast-moving environment.

Qualifications

• 7+ years combined DevSecOps/Platform Engineering/SRE experience.
• Kubernetes administration and development expertise.
• Docker/containerization proficiency.
• Azure or AWS with Terraform or Crossplane.
• Python/Go/Bash for automation.
• Networking: VPC, DNS, TLS, load balancers.
• PyTorch/HuggingFace and AI tooling experience.
• AI workloads on Kubernetes with GPUs.
• AI platform operations and model lifecycle tooling.
• Vector databases, embeddings, RAG, semantic search.
• AI security governance and data handling.

Responsibilities

• Build/operate AI access platform on Kubernetes and containerized services.
• Deploy core AI services and frontier models; design MLOps pipelines.
• Provide expert recommendations for enterprise AI adoption and governance.
• Collaborate with security and DevSecOps teams to maintain compliance.

Skills

Kubernetes mastery

Containerization

Cloud platforms (Azure/AWS)

Programming (Python/Go/Bash)

Networking knowledge

AI/ML frameworks

GPU-enabled Kubernetes

MLOps concepts

CI/CD (GitLab)

Vector databases/RAG

AI security/governance

GitLab CI/CD

Education

DoD 8570 certifications (e.g., Security+ or CASP+)

Tools

Kubernetes

Docker

ArgoCD

Helm

Terraform

Crossplane

Istio

Keycloak/OIDC

Grafana/Prometheus

vLLM

GitLab

Job description

Clarity Innovations, a government-focused technology partner, is seeking a Platform Engineering Architect to advance AI capabilities across the enterprise stack.

You will own the AI access platform on Kubernetes, deploy AI services, integrate frontier models, and shape MLOps pipelines while ensuring security and governance in national security contexts. This role demands deep Kubernetes, CI/CD, and cloud expertise in a fast-moving environment.