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 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

Required Skills & Experience

• 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 Have

• 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