Job Description
Location: Dayton, OH (preferred) | Remote Eligible (CAC Access Required) Clearance: TS/SCI Preferred Build the Infrastructure That Makes AI Mission-Ready As a Platform Engineer, you will design and operate the infrastructure that enables AI/ML systems to function in real-world mission environments supporting classified, mission-critical programs. You won’t just build platforms: you’ll bridge the gap between AI development and operational deployment, ensuring systems scale, integrate, and perform under real constraints. What You’ll Do Architect and operate Kubernetes-based platforms supporting AI/ML workloads Build and manage containerized environments (Docker, Helm, OCI) for scalable deployment Design and optimize data pipelines for ingestion, transformation, and model lifecycle support Integrate AI/ML services into secure, mission-critical systems Develop Infrastructure as Code (Terraform, Ansible) for repeatable, compliant environments Build and enhance CI/CD pipelines (GitLab, Jenkins, GitHub Actions) Implement observability and monitoring (Prometheus, Grafana) to ensure system health and performance Collaborate cross-functionally to translate complex requirements into deployable systems Solve engineering challenges within classified and constrained environments What You Bring Strong experience with Kubernetes and cloud-native platform engineering Hands-on experience with containerization (Docker, Helm) Experience supporting data pipelines or ML-enabled systems Familiarity with Infrastructure as Code (Terraform, Ansible) Experience with CI/CD and DevSecOps practices Understanding of distributed systems and system integration Ability to operate effectively in secure or regulated environments Clearance Requirements Active TS/SCI clearance strongly preferred Candidates with an active Secret clearance may be considered and supported for upgrade Candidates without an active clearance must be: U.S. citizens eligible to obtain and maintain a clearance able to work in a CAC-enabled or secure environment Note: Start timelines and work scope may vary depending on clearance status and program requirements Why This Role Matters In many environments, AI stops at experimentation; in this role, you ensure it becomes operational capability. You Will Enable AI/ML systems to move from development to deployment Support mission-critical operations tied to national security Work at the intersection of cloud-native engineering, DevSecOps, and AI infrastructure Build systems where failure is not an option and performance is essential Your work directly impacts how advanced technology is applied in real-world scenarios. What You’ll Gain Hands-on ownership of platforms powering AI/ML in mission environments Exposure to complex, high-scale distributed systems Experience integrating modern cloud-native technologies into secure, real-world systems Growth across platform engineering, DevSecOps, and AI infrastructure The opportunity to solve problems most engineers never encounter About Rackner Rackner is a software consultancy that builds cloud-native solutions for startups, enterprises, and the public sector. We are an energetic, growing consultancy focused on solving complex problems through distributed systems, DevSecOps, AI/ML, and modern systems architecture. We enable digital transformation by applying cloud-first, cost-effective innovation across mission-critical environments. Our customers span a diverse and growing set of industries, and our teams are driven by a shared focus on end-to-end system delivery and real-world impact. Benefits & Perks Rackner invests in your growth, stability, and long-term success: Paid certifications & professional development 401(k) with 100% match up to 6% Highly competitive PTO Comprehensive Medical, Dental, Vision coverage Life Insurance + Short & Long-Term Disability Home office & equipment plan Industry-leading weekly pay schedule #PlatformEngineering #Kubernetes #DevSecOps #AIInfrastructure #MachineLearningOps #CloudNative #DefenseTech #ClearedJobs #NationalSecurity #InfrastructureEngineering #DistributedSystems #Terraform #Docker #DataEngineering #MLOps