Full-Stack Platform Engineer
OpenTeams
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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. Full-Stack Platform Engineer x2 Location: U.S - Remote OR Hybrid - Washington, DC, Denver, CO or Colorado Springs, CO. Work Authorization: U.S. citizenship required 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. Salary Range: $145,000–$250,000 USD, dependent on experience level and location Openings: Two positions are available: 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. Candidates will be considered for the opening that best aligns with their location, clearance status, experience, and work preferences. Candidates who meet the requirements for multiple openings may be considered for more than one. About the Role We're looking for a Full-Stack Platform Engineer to build both sides of an AI platform — the API surface other teams build on, and the interfaces analysts use directly. The API comes first here, and that's a real constraint rather than a slogan: platform capabilities are consumed through documented interfaces by analysts, internal teams, and partner organizations using their own tools. If those interfaces are unstable or hard to reason about, adoption stalls regardless of what the platform can do underneath. On the backend, you build API-first services for workflow orchestration, data ingestion, evaluation execution, and results management, and you implement identity federation and access controls that hold up across deployment environments. On the frontend, you build the analyst-facing tooling — modern web consoles and utilities where someone actually kicks off a workflow, inspects a result, or figures out why a run failed. You should be comfortable in a component-based web stack, though the emphasis is on clear, functional interfaces over visual polish. Doing both sides means you feel your own API design decisions from the consuming side, which is the fastest way to find the ones that were wrong. You also produce what external teams need to build on the platform: documentation, reference implementations, and client examples that work when someone follows them. Key Responsibilities Design, implement, document, and maintain APIs for workflow orchestration, data ingestion, evaluation execution, and results management Define clear, stable, and versioned interface specifications for use by external integrators Implement brokered single sign-on and identity federation using protocols such as OpenID Connect, SAML, and PKI/X.509 certificate-based authentication Enforce approved authentication, authorization, and access-control requirements across platform services Design relational data models that support platform APIs and workflow requirements Build the analyst-facing web interfaces for the…
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