AI/ML Cloud Engineer (TS/SCI Polygraph Required)

Role: Senior AI/ML Cloud Engineer (TS/SCI Polygraph Required) Location: Remote w/ occasional travel D.C A high-growth AI infrastructure company is hiring a an AI/ML Cloud Engineer to support federal, defense, and intelligence-community customers. This person will own technical pre-sales engagements, run complex evaluations, and help agencies deploy secure cloud-development and AI-enabled developer environments—including in classified, disconnected, and air-gapped networks. The role blends solutions architecture, technical sales, Kubernetes/platform engineering, customer success, and emerging AI developer-tooling expertise. The right person can earn credibility with deeply technical stakeholders while translating infrastructure decisions into mission outcomes. What You’ll Do Own the technical relationship with prospective government customers throughout the pre-sales cycle and drive evaluations toward a successful technical outcome. Lead technical discovery, architecture discussions, demos, workshops, and proof-of-concepts for secure developer-platform deployments. Demonstrate the platform from developer, administrator, and AI-agent workflow perspectives. Install, configure, and troubleshoot developer infrastructure across cloud, government cloud, on-premises, Kubernetes, virtual-machine, disconnected, and air-gapped environments. Design and execute proof-of-concepts that validate platform value for secure software development and AI-assisted or agentic development workflows. Partner with account teams and customers to overcome technical blockers, accelerate evaluations, and support deal progression. Provide post-sales technical support, adoption guidance, renewal support, and escalation management as needed. Troubleshoot Kubernetes, Linux, networking, deployment, access, proxy, ingress, load-balancing, and infrastructure issues in restricted-access environments. Serve as the voice of federal customers, translating field feedback, product gaps, and feature requests into actionable input for Product and Engineering. Contribute deployment guidance, reference architectures, technical documentation, and product feedback to internal and external repositories. Become a trusted subject-matter expert in cloud development environments, secure developer platforms, coding agents, and AI-enabled software-delivery workflows. Required Qualifications Active TS/SCI clearance with Polygraph at the time of hire. U.S. citizenship and current residence in the DC/Maryland/Virginia area, with the ability to travel to customer sites. 5+ years of Solutions Engineering, Sales Engineering, Solutions Architecture, Technical Account Management, or customer-facing infrastructure engineering experience. Experience supporting federal, defense, intelligence-community, or other highly regulated government customers. Strong Linux administration and command-line experience. 3+ years of hands-on Docker and Kubernetes experience. 3+ years of Terraform or comparable infrastructure-as-code experience. Experience deploying or supporting infrastructure in AWS GovCloud, Azure Government, on-premises, private-cloud, disconnected, or air-gapped environments. Strong networking knowledge, including proxies, ingress controllers, load balancers, routing, DNS, TLS, identity/access considerations, and network boundaries. Ability to lead technical discovery, live demos, deployment workshops, architecture reviews, and deep-dive troubleshooting with senior technical and program stakeholders. Strong communication skills and an ability to translate complex infrastructure challenges into meaningful mission, security, speed, and developer-productivity outcomes. AI / Agentic Requirements Hands-on familiarity with AI coding tools and developer assistants, such as Claude Code, GitHub Copilot, Cursor, or comparable tools. Understanding of how engineering teams use coding agents and LLM-powered development workflows in practice. Experience discussing or supporting LLM infrastructure concepts, including model gateways, model proxies, routing layers, API access controls, and tools such as LiteLLM or similar platforms. Ability to speak credibly about how federal and intelligence customers evaluate, secure, govern, and deploy AI-enabled developer tooling—particularly in classified or isolated environments. Interest in helping agencies adopt agentic development workflows where they offer a practical and mission-aligned benefit.