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. citizenship and ability to obtain and maintain a Secret security clearance

6+ years of hands-on infrastructure, platform, DevOps, or site reliability engineering experience supporting production systems

Strong understanding of infrastructure engineering principles, including scalability, reliability, observability, security, and automation

Production experience with Kubernetes, including workload scheduling, resource management, and multi-tenant environments

Experience with automated security tooling, such as container scanning, SAST/DAST, artifact signing, and policy enforcement

Proficiency with infrastructure-as-code tools such as Terraform, OpenTofu, Pulumi, or equivalent technologies

Experience with at least one major cloud platform—AWS, Azure, or Google Cloud—including networking, security, storage, and compute services

Experience implementing monitoring and observability using tools such as OpenTelemetry, Prometheus, Grafana, or equivalent technologies

Strong programming or automation skills using Python, Go, or a comparable language

Experience with CI/CD practices, GitOps workflows, and infrastructure automation

Experience creating maintainable operational documentation, deployment procedures, and runbooks

Experience leading technical initiatives, establishing engineering practices, or mentoring other engineers

Ability to work independently and collaborate effectively within a remote, distributed team

Ability to give and receive constructive technical feedback

Nice to Have

Experience deploying or operating infrastructure in air-gapped, disconnected, or highly restricted environments

Experience engineering systems subject to the Risk Management Framework, NIST 800-53, NIST 800-171, or comparable security requirements

Experience supporting security personnel in achieving an Authorization to Operate for complex systems in Government or Intelligence Community environments

Experience supporting systems operating at Impact Level 5 or higher

Current DoD 8140 qualifying certification, such as Security+, CISSP, CISM, or an equivalent IAT/IAM Level II or III credential

Experience building MLOps pipelines or infrastructure supporting AI/ML workloads

Experience with GPU scheduling, large-scale data pipelines, or reproducible ML evaluation workloads

Experience with model-serving frameworks such as KServe, vLLM, LLM-D, or equivalent technologies

Familiarity with data sovereignty, privacy, and security requirements for enterprise or Government AI systems

Contributions to open-source Kubernetes, infrastructure, MLOps, or observability projects

Experience with Nebari

What We Offer

Medical, Dental & Vision – 100% paid for employees, 75% for dependents

401(k) Match – Up to 5% with full vesting after 2 years

Unlimited PTO – With a required minimum of 15 days off annually

Fully Remote Setup – Includes up to $3,000 equipment reimbursement

Continuous Education – Includes up to $500 reimbursement

Disability & Life Insurance – 100% employer-paid

HSA & FSA Options – With monthly HSA contributions from OpenTeams

Grow With Us

At OpenTeams, growth isn’t just about the company—it’s about you.

We believe the best careers are built at the edge of your potential. That is where new tools, ideas, and technologies change the world. Here, you’ll work alongside pioneers of AI, solving problems that matter: making AI more transparent, more ethical, and more empowering. As your skills grow, our career framework provides a pathway and recognition of that increased impact.

Opportunities aren’t limited by geography. You’ll collaborate with global experts, contribute to open source projects that power the world’s technology, and stretch your skills daily. That global perspective and diversity makes our solution more universal and robust. We are committed to continuing to celebrate diversity on our team.

Supported people are successful people. We offer 100% e