Senior Software Engineer, Full Stack, Google Public Sector

Senior Software Engineer, Full Stack, Google Public Sector

Google Boulder, CO, USA ;
Reston, VA, USA ; +1 more

The application window will be open until at least March 16, 2026. This opportunity will remain online based on business needs which may be before or after the specified date. Must be a US Citizen to meet customer and compliance requirements, including potential access to classified information.

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
Boulder, CO, USA;
Reston, VA, USA;
Washington D.C., DC, USA
.

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience in software development, including testing, maintaining, and launching software products.
• 3 years of experience testing, maintaining, or launching software products.
• Experience with Kubernetes and containerized environments.
• Active, or the ability to obtain, a Top Secret security clearance.

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;

the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The GPS AI Catalyst Team (ACT) is dedicated to supercharging AI adoption across the public sector. By tightly aligning our engineering efforts with Go-to-Market and Google Public Sector Services, we incubate and productionalize differentiated AI solutions to solve repeatable mission‑critical use cases. We serve as the technical backbone and trusted advisors for customers, ensuring the swift and secure integration of AI solutions, from initial concept through sustained deployment.

Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.

The US base salary range for this full‑time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Lead the development of full‑stack prototypes and production‑ready applications for greenfield AI projects, ensuring seamless integration between intuitive front‑ends and robust back‑ends.
• Partner with GPS Sovereign Engineering and Google Distributed Cloud (GDC) teams to identify mission‑critical pain points and architect AI‑driven solutions for restricted environments.
• Drive architectural designs and exercise high‑level technical judgment when selecting frameworks, ensuring AI models and data pipelines are performant and secure.
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