Senior Infrastructure Engineer - AI/ML Platform

Who We Are Every organization runs on intelligence: years of accumulated knowledge, decisions, and context. As AI takes on more of that work, companies face a choice: rent that intelligence from vendors who keep the data, the context, and the results, or own it. OpenTeams exists to make ownership possible. Founded by Travis Oliphant, creator of NumPy and SciPy, and built by people with deep roots across the open-source ecosystem, including NumPy, SciPy, PyTorch, and Jupyter, we help enterprises and governments build AI they control, govern, and evolve themselves. If that sounds like your kind of work, we'd like to meet you. Senior Infrastructure Engineer - AI/ML Platform Location: U. S - Remote Work Authorization: U. S. citizenship required Clearance: An active clearance is not required at the time of hire. Candidates must be able to obtain and maintain a Secret security clearance, which includes a federal background investigation.

Salary Range: $145,000–$250,000 USD, dependent on experience level and location About the Role We’re seeking a Senior Infrastructure Engineer to build and operate the platform underlying secure AI test and evaluation capabilities for Government teams assessing AI systems. You’ll own a Kubernetes-based platform supporting demanding AI/ML workloads, including GPU scheduling, large-scale data movement, reproducible test execution, and multi-tenant isolation. The platform must operate reliably within Government environments that may have restricted networks, accreditation boundaries, limited connectivity, and no assumption of outbound internet access or managed cloud services. You’ll use open-source technologies such as OpenTofu, Terraform, Helm, Argo CD, Kubernetes operators, and Nebari to build reusable and composable infrastructure. You’ll also own platform reliability, observability, capacity planning, upgrade paths, hardened configurations, and the documentation needed to deploy and maintain the platform. This is a fully remote, U. S. -based role working with a distributed team that relies heavily on asynchronous communication. Key Responsibilities - Build and operate the Kubernetes platform supporting AI test and evaluation frameworks - Implement GPU scheduling, workload orchestration, resource management, and multi-tenant isolation across evaluation teams - Design infrastructure-as-code, GitOps workflows, and automated deployment pipelines that make the platform reproducible from source - Develop reusable and modular infrastructure components that can be composed into independently owned and operated platforms - Contribute to Nebari and other open-source Kubernetes, infrastructure, and MLOps projects used by the platform - Own platform reliability, including capacity planning, upgrade strategies, failure-mode analysis, backup and recovery considerations, and operational readiness - Design and implement observability, monitoring, logging, tracing, and alerting for large-scale AI/ML workloads - Develop operational runbooks and documentation that enable other engineers to deploy, operate, and troubleshoot the platform - Deploy, configure, and harden infrastructure within secure, restricted, disconnected, or limited-connectivity Government environments - Support security authorization and compliance activities through infrastructure documentation, hardened configurations, control evidence, and repeatable deployment processes - Integrate automated security tooling for container scanning, static and dynamic analysis, artifact signing, and policy enforcement - Collaborate with Government stakeholders, security personnel, software engineers, and ML engineers to translate platform requirements into reliable infrastructure - Provide technical leadership, contribute to engineering standards, and mentor less-experienced team members - Collaborate effectively within a remote and distributed team using asynchronous communication practices Required Skills & Experience - U. S.