Platform Engineer (Cloud-Native AI/ML Systems Integration)

Platform Engineer (Cloud-Native AI/ML Systems Integration)
Location: Dayton, OH (preferred) | Remote Eligible (CAC Access Required)
Clearance: TS/SCI Preferred

Build the Infrastructure That Makes AI Mission-Ready
This is not a typical engineering role. As a Platform Engineer, you will design and operate the infrastructure that enables AI/ML systems to function in real-world mission environments. Your work will directly support Air Force / NASIC-aligned programs, where performance, security, and reliability are non-negotiable.

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

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