Senior Principal Platform Engineer
Architects and operates the AI 'plumbing' for Intelligence Community and DoD missions: a Kubernetes-based platform providing unified access to frontier models (Claude, GPT) and local inference (vLLM). Day to day: GitLab CI/CD, ArgoCD GitOps, Helm, Terraform on Azure/AWS, plus MLOps pipelines and securing GPU-enabled AI workloads.
- Compensation
- $123K–$322K / yr
- Location
- Jessup, MD
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Contract
- Experience
- 7+ years
- Category
- Devops
- Posted
Skills
Must have
- 7+ years combined experience in DevSecOps, Platform Engineering, or SRE
- Deep expertise in administration and development of Kubernetes clusters
- Advanced knowledge of Docker or equivalent container build tools
- Experience with Azure or AWS architecture
- Experience with Infrastructure as Code (Terraform/Crossplane)
- Proficiency in at least one backend or scripting language (ideally Python, Go, or Bash)
- Solid understanding of OSI Layer 4-7, including VPC/VNET, DNS, load balancing, and SSL/TLS management
- Practical experience with modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, vLLM, Ray, or MLflow
- Hands-on experience deploying, scaling, and securing AI/ML workloads on Kubernetes, including GPU-enabled clusters and model-serving platforms
- Experience building internal AI platforms or developer enablement tooling for model lifecycle management and inference endpoints
- Familiarity with MLOps concepts and tooling, including automated model deployment, versioning, evaluation, observability, rollback, and CI/CD integration
- Working knowledge of vector databases, embedding pipelines, RAG, and semantic search architectures
- Understanding of AI security concerns: model isolation, data handling controls, prompt injection, supply-chain security, and governance
- Mastery of GitLab CI/CD (Runners, Templates, Security Scanners)
- Hands-on experience with ArgoCD or equivalent declarative CD tools
- Proficiency with Helm for templating and deploying Kubernetes applications
Nice to have
- DoD 8570 certifications (e.g., Security+ or CASP+/SecurityX)
- Experience with Service Mesh technologies (e.g., Istio, Cilium) and CNI plugins
- Configuration and management of Keycloak or OIDC/SAML providers
- Experience with the Grafana/Prometheus stack or similar observability tooling
- Functional knowledge of PostgreSQL and MySQL administration
- Experience maintaining data pipelines or high-throughput data infrastructure
- Background in threat modeling, vulnerability management, or SOC operations
- Experience designing or maintaining RESTful or RPC APIs
Full description
Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world.
Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact.
We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security.
As a Platform Engineering Architect you will focus on operationalizing, securing, and maturing artificial intelligence capabilities by building and maintaining the AI "path-to-prod" and a scalable AI run stack—the AI “plumbing.” Your work centers on providing a unified interface for AI model access, integrating foundational and reasoning models, AI agents, and generative AI. Key responsibilities include contributing to the K8s-based AI access platform, managing deployment of core AI services, integrating frontier models (e.g., Claude, GPT) and local inference engines (e.g., vLLM) along with designing MLOps pipelines. The role also requires providing expert recommendations for enterprise AI adoption, specifically in agentic orchestration and spec-driven development.
Core Requirements
· Professional Experience: 7+ years of combined experience in DevSecOps, Platform Engineering, or SRE.
· Kubernetes Mastery: Deep expertise in Administration and Development of Kubernetes clusters.
· Containerization: Advanced knowledge of Docker or equivalent container build tools.
· Cloud & IaC: Experience with Azure or AWS architecture and Infrastructure as Code (Terraform/Crossplane).
· Software Development: Proficiency in at least one backend or scripting language—ideally Python, Go, or Bash—to drive systems automation.
· Core Networking: Solid understanding of OSI Layer 4–7, including VPC/VNET configuration, DNS, Load Balancing, and SSL/TLS management.