Platform Engineer

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
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

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