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

Job Description

Role: Senior AI/ML Cloud Engineer (TS/SCI Polygraph Required)

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Location: Remote w/ occasional travel D.C

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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.

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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.

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What You’ll Do

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• Own the technical relationship with prospective government customers throughout the pre-sales cycle and drive evaluations toward a successful technical outcome.
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• Lead technical discovery, architecture discussions, demos, workshops, and proof-of-concepts for secure developer-platform deployments.
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• Demonstrate the platform from developer, administrator, and AI-agent workflow perspectives.
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• Install, configure, and troubleshoot developer infrastructure across cloud, government cloud, on-premises, Kubernetes, virtual-machine, disconnected, and air-gapped environments.
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• Design and execute proof-of-concepts that validate platform value for secure software development and AI-assisted or agentic development workflows.
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• Partner with account teams and customers to overcome technical blockers, accelerate evaluations, and support deal progression.
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• Provide post-sales technical support, adoption guidance, renewal support, and escalation management as needed.
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• Troubleshoot Kubernetes, Linux, networking, deployment, access, proxy, ingress, load-balancing, and infrastructure issues in restricted-access environments.
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• Serve as the voice of federal customers, translating field feedback, product gaps, and feature requests into actionable input for Product and Engineering.
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• Contribute deployment guidance, reference architectures, technical documentation, and product feedback to internal and external repositories.
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• Become a trusted subject-matter expert in cloud development environments, secure developer platforms, coding agents, and AI-enabled software-delivery workflows.
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Required Qualifications

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• Active TS/SCI clearance with Polygraph at the time of hire.
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• U.S. citizenship and current residence in the DC/Maryland/Virginia area, with the ability to travel to customer sites.
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• 5+ years of Solutions Engineering, Sales Engineering, Solutions Architecture, Technical Account Management, or customer-facing infrastructure engineering experience.
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• Experience supporting federal, defense, intelligence-community, or other highly regulated government customers.
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• Strong Linux administration and command-line experience.
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• 3+ years of hands-on Docker and Kubernetes experience.
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• 3+ years of Terraform or comparable infrastructure-as-code experience.
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• Experience deploying or supporting infrastructure in AWS GovCloud, Azure Government, on-premises, private-cloud, disconnected, or air-gapped environments.
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• Strong networking knowledge, including proxies, ingress controllers, load balancers, routing, DNS, TLS, identity/access considerations, and network boundaries.
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• Ability to lead technical discovery, live demos, deployment workshops, architecture reviews, and deep-dive troubleshooting with senior technical and program stakeholders.
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• Strong communication skills and an ability to translate complex infrastructure challenges into meaningful mission, security, speed, and developer-productivity outcomes.
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AI / Agentic Requirements

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• Hands-on familiarity with AI coding tools and developer assistants, such as Claude Code, GitHub Copilot, Cursor, or comparable tools.
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• Understanding of how engineering teams use coding agents and LLM-powered development workflows in practice.
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• 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.
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• 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.
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• Interest in helping agencies adopt agentic development workflows where they offer a practical and mission-aligned benefit.
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