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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Platform Engineer, AI/ML Infrastructure - **Company:** Openteams, Inc. - **Location:** Colorado Springs, CO, United States (Remote available) - **Experience:** Experienced - **Salary:** $120,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Big Data, Continuous Integration, Distributed Systems, Python (Programming Language), Open Source Technology, Rapid Prototyping Process, Runbook, Data Logging, Pulumi, Google Cloud, Cloud Platform System, Large Language Models, SC Clearance, Containerization, Kubernetes, Machine Learning Operations, Api Design, Terraform, Data Pipelines, Golang - **Published:** September 29, 2026 - **Apply:** https://startup.jobs/platform-engineer-ai-ml-infrastructure-openteams-10182381 ## About the Role Clearance: U.S.-Remote Opening: An active clearance is not required. Candidates must be eligible and willing to obtain and maintain a U.S. security clearance. Hybrid Opening: An active TS/SCI clearance is preferred. Candidates may also be considered if they previously held a TS/SCI with CI polygraph or currently hold an active TS or Secret clearance., * One hybrid position: Candidates must be located in or willing to work hybrid from Washington, DC; Denver, CO; or Colorado Springs, CO. An active TS/SCI clearance is required. Up to 15% travel is required. * One U.S.-remote position: Candidates may work remotely from anywhere in the United States. An active clearance is not required, but candidates must be willing and able to undergo the process required to obtain and maintain a U.S. security clearance., * U.S. citizenship, and the ability to obtain and maintain a U.S. security clearance * Four or more years of hands-on experience building or operating production infrastructure, platforms, or distributed systems * Production experience with Kubernetes and containerized workloads * Experience with at least one major cloud platform: AWS, Azure, or Google Cloud * Experience with infrastructure as code and CI/CD, using tools such as Terraform, OpenTofu, Pulumi, or Helm * Working proficiency in Python, Go, Bash, or a comparable language * Experience implementing or operating production monitoring and observability * Ability to write documentation, runbooks, and deployment procedures that other people can actually follow * Ability to work independently and collaborate well in a remote, distributed team, * An active U.S. security clearance, particularly TS/SCI with CI polygraph * Experience deploying or operating software in air-gapped, disconnected, or otherwise restricted environments * Experience with Department of Defense, Intelligence Community, or comparably regulated programsFamiliarity with the Risk Management Framework, NIST 800-53 or 800-171, or similar frameworks, and with producing the evidence they require * Experience supporting an Authorization to Operate, or with continuous ATO modelsSupply chain security work: hardened images, artifact signing, SBOM generation, dependency and container scanning, policy enforcement * Familiarity with cross-domain solutions, guards, data diodes, or similar transfer mechanisms * Experience with classified cloud environments, including AWS Secret or Top Secret regionsA DoD 8140/8570 qualifying certification such as Security+, CISSP, CASP+, or CISM, or willingness to obtain one after joining * Experience building MLOps pipelines or infrastructure for AI/ML workloads * Experience with GPU scheduling, distributed inference, or large-scale data and evaluation pipelines * Experience with model-serving or gateway frameworks such as KServe, vLLM, or LLM-DExperience designing API-first services and vendor-agnostic platforms that run across multiple environments * Experience with agentic workflow frameworks or multi-step AI pipeline orchestration * Contributions to open-source Kubernetes, infrastructure, MLOps, or observability projects, and experience with Nebari specifically * Familiarity with data sovereignty and privacy requirements for enterprise or government AI systems * Experience leading technical initiatives, setting engineering standards, or mentoring other engineers * Experience supporting rapid prototyping programs or defense innovation initiatives ## Description * Build and operate Kubernetes-based infrastructure for demanding AI/ML workloads, including GPU scheduling, resource management, and multi-tenant isolation * Design and implement platform services for orchestration, data ingest, model serving, and results management behind documented APIs * Write infrastructure as code and build GitOps pipelines so environments are reproducible from source * Build and operate CI/CD pipelines that produce versioned, signed, scanned release artifacts along with the documentation needed to deploy them * Own reliability: capacity planning, upgrade paths, failure-mode analysis, backup and recovery, incident response, and postmortems * Implement monitoring, logging, tracing, and alerting, and define the service level objectives they're measured against * Deploy and validate the platform in restricted, disconnected, or limited-connectivity environments, and verify parity after each release * Keep the platform portable by constraining dependencies to what's confirmed available in target environments * Write runbooks and operational documentation that other engineers can execute without you in the room * Contribute to Nebari and other open-source infrastructure, Kubernetes, and MLOps projects * Work with security engineers, government stakeholders, and other engineers to turn requirements into systems that hold up * Collaborate asynchronously across a distributed team