We are looking for a Senior Solutions Engineer, Federal/Public Sector to join our Solutions Engineering team. You will partner with Account Executives to qualify, progress, and close revenue opportunities with civilian, defense, and intelligence community agencies, guiding them through demos, architecture discussions, and proofs-of-concept that prove Coder’s value for both human developers and the AI coding agents working alongside them, often inside classified or air-gapped networks.

This is not a scripted-demo-only role. You are equally comfortable running a deep technical proof-of-concept inside a disconnected or classified environment and stepping back to translate a technical win into a business case a federal decision-maker will act on. You are energized by ambiguity, motivated by winning deals the right way, and capable of bringing the voice of the agency back into how Coder builds and sells.

What You’ll Do

Own the technical relationship with agency prospects through pre-sales, and efficiently manage towards a technical win

Lead or support post-sales relationships and renewals when needed

Demo the Coder platform from the developer, administrator, and AI agent workflow perspectives, including in classified and air-gapped settings

Install Coder on cloud (including GovCloud) and on-prem Kubernetes or VM infrastructure, up to and including air-gapped and disconnected networks

Run proofs-of-concept that prove Coder’s value, including for agentic and LLM-powered development workflows, and accelerate deals

Evolve into a subject-matter expert on Cloud Development Environments, agentic AI development, and their impact on mission delivery

Serve as the agency’s voice, routing insights to Engineering and Product

Log feature requests and issues in our public/private Git repositories

Troubleshoot Coder deployments, networking, and Kubernetes components during evaluation, including within classified networks

Contribute pull requests to Coder’s documentation

What We’re Looking For

Active TS/SCI clearance with Polygraph required at time of hire; U.S. citizenship required

Physically based in the DC / Maryland / Virginia (DMV) area, with ability to travel to customer sites as required

Minimum 5 years of experience as a Solutions Engineer selling infrastructure or developer tooling, ideally into federal, defense, or intelligence community customers

Experience with AI tooling at both the user level and infrastructure level, including coding agents and assistants (e.g. Claude Code, GitHub Copilot, Cursor) as well as LLM infrastructure such as model proxies and LLM routing layers (e.g. LiteLLM), and the ability to speak credibly to how agencies evaluate and adopt them, including in classified environments

Strong customer-facing skills that win trust with technical stakeholders and program offices

Ability to translate technical hurdles into mission value in real time

Understand agentic AI software development use cases and advocate passionately where appropriate

Comfortable leading architecture demos and deep-dive troubleshooting sessions in secure, restricted-access environments

Deep Linux fundamentals and comfort at the command line

3+ years hands-on with Docker and Kubernetes

Experience with AWS GovCloud, Azure Government, or on-prem/air-gapped Kubernetes deployments

3+ years with Terraform or comparable infrastructure-as-code tooling

Solid grasp of networking: ingress controllers, proxies, load balancers, and operating within DoD/IC network boundaries

Startup-speed execution, ownership mindset, and a player-coach attitude

What Success Looks Like

You can walk into an ambiguous agency conversation, diagnose the real technical, security, and mission blockers, and design a proof-of-concept that proves value fast, even inside a classified network.

You translate deep technical fluency, including on agentic and LLM-based development workflows, into a business case that resonates with program managers, security officers, and mission owners alike.

Agencies leave your demos and PoCs with a clear, credible picture of how Coder fits their environment, their developers, and their AI agents, without compromising their security posture.