Software Engineer, Federal

Description

The company builds a platform that lets large enterprise engineering teams run their software organizations as autonomous software factories, where tools ship code, review pull requests, run tests and deploy continuously.

Customers include Nvidia, Blackstone, Royal Bank of Canada (RBC), Palo Alto Networks, Adobe and T-Mobile.

In 2026 the company raised $200M at a $5B valuation, bringing total funding to over $400M. Investors include Khosla Ventures, Sequoia, Blackstone, Ali Ghodsi (CEO of Databricks) and Frank Slootman (former CEO of Snowflake).

This is a founding role on a new Federal team. You will build AI systems that help government software organizations work faster, and you will bring the platform into secure, classified and air-gapped environments for the Department of War, the Intelligence Community and federal civilian agencies.

Responsibilities

• Design, build and ship AI agent systems that extend the platform's core AI features for federal missions.
• Deploy and harden the platform in GovCloud, on-premises, classified and fully air-gapped networks, where connectivity may be limited or absent and models are self-hosted or government-approved.
• Build security and compliance in from the start, working with Security and Infrastructure to reach and keep FedRAMP High and DoD Impact Levels IL5/IL6, including access controls, audit logging and continuous monitoring.
• Add layered guardrails, observability and explainability to agents so government users can trust, audit and follow how an agent produced its output.
• Work with federal customers, on site when needed, to learn their missions and workflows, set requirements with stakeholders, and take delivery from first prototype to accepted production.
• Connect the platform to the tools government engineering teams already use, such as on-premises source control, CI/CD pipelines, ticketing systems and DoD software factories.
• Partner with product, engineering and Federal go-to-market teams to turn new AI research into practical solutions for missions.
• Prototype quickly and refine AI features using feedback from real users, including government developers and program offices.
• Find and fix stability and scaling problems so the platform performs reliably under heavy load in high-stakes, resource-limited settings.
• Lead work on large-scale data processing to make the AI systems more reliable and effective.
• Carry field findings back into the core platform so that features built for one mission can be reused across the public sector.
• Help build the Federal team from the ground up, working with leadership on technical proposals, capture strategy and the public sector product roadmap.

Requirements

• At least 2 years of hands-on software engineering experience after earning a Bachelor's or Master's degree in Computer Science, Engineering, AI or a related technical field.
• Proven skill with LLMs and a record of applying AI or ML to hard, unstructured problems, ideally in software engineering or a related area.
• Self-motivated and able to take unclear projects from idea to impactful deployment, ideally on a founding team, a new initiative or a forward-deployed engineering group.
• Clear communicator who can explain technical ideas and strategy to anyone, including non-technical government stakeholders, with an innovative strategic outlook.
• Comfortable working directly with customers, including spending time at their sites.
• Genuine interest in public sector work and belief that government can deliver better outcomes through technology.
• Preferred: experience deploying software in regulated or secure environments such as AWS GovCloud, Azure Government, FedRAMP, DoD Impact Levels or classified and air-gapped networks. Not required.
• Preferred: familiarity with government work, including procurement, compliance and the ATO accreditation process.
• Preferred: experience with data-intensive applications and the software development lifecycle. Not required.

Conditions

Location is flexible. Candidates based in San Francisco, CA (HQ) are preferred, as are candidates in Washington, D.C., which is listed as remote.