AI Forward Deployed Engineer

Senior Forward Deployed Engineer – Public Sector Washington, DC or San Francisco, CA (no other locations or fully remote options)

Compensation: $167,000–$203,000 base salary + equity, benefits, and incentive compensation

Employment Type: Full-Time | Individual Contributor

Travel: Up to 50%, including regular on-site customer engagement

Our client is a venture-backed AI security company helping government and enterprise organizations deploy AI safely and securely. Its platform enables customers to evaluate AI models and applications, protect sensitive data, enforce runtime policies, govern AI agent behavior, and maintain the documentation needed for oversight and compliance. The platform supports cloud, hybrid, on-premises, edge, and air-gapped environments. The company is now building out its dedicated public sector organization, offering an opportunity to help shape how its technology is deployed across government and national security environments.

Our client is seeking a Senior Forward Deployed Engineer to help public sector customers deploy and operationalize its platform in mission-critical environments. This is a hands-on engineering role at the intersection of software development, customer deployment, AI assurance, and government technology. You'll write code, debug complex systems, build integrations, support deployments, and develop demos, prototypes, and workflows that help customers put AI security capabilities into practice. Working directly with customer engineering teams, mission users, security stakeholders, and internal product and engineering teams, you'll translate operational needs into working software and practical deployment architectures. You'll also bring real-world customer feedback back to the team to inform product development and public sector strategy.

Develop deep expertise in the company's AI evaluation, runtime guardrail, and agent governance platform. Work directly with federal customers to understand mission requirements, technical challenges, and operational constraints, translating them into solution architectures, integrations, and implementation plans. Help customers move from validated use cases and initial evaluations to working deployments. Deploy, integrate, and support the platform across cloud, hybrid, on-premises, air-gapped, and government-controlled environments. Write code, troubleshoot complex technical issues, and resolve implementation challenges alongside internal engineering, platform, security, and customer teams. Collaborate with product and engineering teams to improve integrations, deployment processes, and platform capabilities. Share field insights with product, engineering, research, and go-to-market teams to inform the roadmap, deployment strategy, and future customer requirements.

5+ years of experience in customer-facing engineering roles, including forward deployed, solutions, sales, product, or implementation engineering.

Strong coding skills in Python and experience with TypeScript, Java, Go, Bash, or similar languages.

Experience building, deploying, integrating, or operating production software across cloud, containerized, on-premises, or enterprise environments.

Working knowledge of AI/ML systems, including generative AI, LLM applications, model evaluation, guardrails, observability, or agentic workflows.

Strong debugging and problem-solving skills, with the ability to work through complex technical challenges in live customer environments.

Ability to translate customer requirements into practical technical solutions and communicate complex concepts to both technical and non-technical audiences.

Ability to collaborate across engineering, product, security, and customer teams.

Willingness to travel regularly to customer sites, with travel reaching up to 50%.

S. security clearance.

Experience supporting Department of War, Intelligence Community, federal civilian, or other public sector customers. Familiarity with RMF, FedRAMP, Impact Level (IL) environments, ATO processes, CMMC, or government software accreditation. Experience with Kubernetes, Docker, Terraform, CI/CD pipelines, cloud infrastructure, platform engineering, or enterprise integrations. Experience integrating with identity and access management (IdAM) providers, SIEMs, data platforms, APIs, secure networks, or logging and monitoring tools. Hands-on experience with AI evaluation, red-teaming, runtime guardrails, model observability, AI governance, or agentic systems. Previous experience at a defense tech, AI, cybersecurity, cloud, or enterprise SaaS company. Active Secret, Top Secret, or TS/SCI clearance.