Full-Stack Platform Engineer

OpenTeams•Denver, WA

3d•Hybrid

About The Position

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. This position is contingent upon contract award. Travel of up to 15% may be required, primarily to Government facilities and between company locations. Unclassified work may be performed remotely, while future classified responsibilities may require an appropriate clearance and onsite work in an accredited facility.

Requirements

U.S. citizenship and eligibility to obtain and maintain a U.S. security clearance
5+ years of full-stack or backend engineering experience, with an emphasis on API-first services
Proficiency in Python, TypeScript, Go, or a comparable programming language
Experience designing, documenting, versioning, and maintaining REST or GraphQL APIs used by external teams or integrators
Working proficiency with a modern component-based frontend framework such as React, Vue, or Svelte, and the ability to build clean, functional interfaces without dedicated design support
Familiarity with the patterns AI interfaces depend on — streaming responses, asynchronous job status, and interfaces that stay usable while an operation is still running
Hands-on experience implementing authentication and authorization using OpenID Connect, SAML, PKI/X.509 certificates, or comparable identity protocols
Experience developing containerized applications and services
Experience with Git-based development workflows, automated testing, and continuous integration
Demonstrated ability to write developer-facing API documentation, integration guides, and reference implementations
Experience with relational databases and API-level data modeling
Ability to translate technical requirements and user feedback into clear, maintainable interface specifications
Strong written communication skills and the ability to support technical users integrating with platform services
Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience

Nice To Haves

Experience building headless platforms, developer platforms, or public API products
Experience building user interfaces on top of LLMs, agents, or other AI/ML services
Experience developing human-in-the-loop review, scoring, annotation, or adjudication tooling
Familiarity with Government identity and access-management standards, including CAC/PIV authentication
Experience developing Jupyter notebooks, SDK examples, or technical enablement materials for analyst and data science audiences
Experience delivering software for Government, defense, or another regulated industry
Experience integrating AI/ML services, model gateways, or evaluation tools through documented API contracts
Familiarity with access-control models such as role-based or attribute-based access control
Familiarity with design systems or component libraries
Active or previously held U.S. security clearance

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 platform — consoles for launching workflows, inspecting results, and diagnosing failed runs
Develop UI for AI-specific interaction patterns: streaming model output, long-running and multi-step agentic runs, prompt and configuration management, and side-by-side comparison of model or workflow results
Ensure analyst-facing interfaces are built strictly on the same public APIs external integrators use, keeping the platform genuinely headless rather than headless in name
Produce and maintain API documentation, integration guides, SDK examples, reference implementations, and example workflows
Develop notebooks and other enablement resources for data science and analyst audiences
Support partner organizations and Government teams integrating with published platform interfaces
Write automated tests and maintain CI pipelines across backend and frontend code
Ensure application dependencies are compatible with target deployment environments
Collaborate with platform, security, infrastructure, and ML engineers to deliver reliable, secure, and interoperable platform services