AI​/ML Platform Engineer

We are seeking a highly skilled AI/ML Platform Engineer to join our Engineering Team supporting Civilian government agency programs. This is not a role for someone who only builds AI solutions it is a role for someone who builds the platforms that enable others to build AI solutions, across all paradigms: traditional ML, Generative AI, and Agentic AI.

The vision is simple: mission teams should be able to focus entirely on their problems and the solutions they want to build and trust that the platform underneath them handles the tools, infrastructure, guardrails, governance, monitoring, and technical complexity. That platform is what this team builds and operates. The right candidate takes genuine satisfaction in being the force multiplier that makes everyone around them more capable.

We welcome engineers from commercial and federal backgrounds alike. If you've built serious AI/ML platforms in industry and want to apply that experience to problems that matter at scale, in a regulated environment, partnering with cloud leaders like AWS and Databricks this is that opportunity. The AI/ML landscape is evolving fast, and we move with it: new capabilities get evaluated, integrated, and delivered to mission teams  right candidate thrives in that environment, stays ahead of it, and drives change rather than waiting for direction.

Equally important is an FDE (Field Delivery Engineer) mindset: partner directly with customers from concept through delivery requirements, specs, design, implementation, production. One engineer, full thread, done. Proactive by default, bringing solutions rather than status, and driving to completion without being managed to it.

• Enable AI/ML platform services as a governed, multi-tenant enterprise offering tenant onboarding, entitlements, access controls, compute environments, and service-level guardrails spanning traditional ML, GenAI, and agentic AI.

• Enable GenAI application building blocks governed access to frontier models via an AI gateway layer, RAG infrastructure (knowledge bases, vector databases, embedding pipelines), per-tenant guardrails, grounding validation, and feedback mechanisms so customers can build GenAI applications on a trusted foundation without reinventing the plumbing.

• Enable agentic AI patterns orchestration frameworks, tool/API integration, memory and state management, human-in-the-loop controls, and safety guardrails so customers can build and run agent-based workflows within the platform's governance boundary.

• Enable traditional ML operationalization governed training environments, model deployment pipelines with TAI controls (bias, fairness, explainability, model cards), and fleet-wide drift and quality monitoring across all operationalized models.

• Partner with customers from concept to delivery own the engagement end to end: requirements, specs, solution design, hands-on implementation, and production handoff. Sit with mission teams, understand their problems, and help them build on the platform.

• Rapidly evaluate and integrate new platform capabilities stay current with the evolving AI/ML landscape, assess new tools and services, and bring the right ones into the platform offering at pace.

• Build platform onboarding patterns and IaC templates (Terraform, Cloud Formation) with SSO integration, designed for repeatability and portability across deployments.

• Develop secure API-based model access and inference endpoints consistent with governance and security standards.

• Document reusable patterns, frameworks, and APIs everything built is a starting point for the next deployment, not a one-off.

• Bachelor’s or master’s degree in computer science, Machine Learning, or a related field.
• 5+ years of hands‑on AI/ML engineering…