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Senior Software Engineer, AI/ML, Technical Delivery, Google Public Sector

Google3,180 open roles

Where
Reston, VA, USA; Washington D.C., DC, USA
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Your applicationOpen nowSenior Software Engineer, AI/ML, Technical Delivery, Google Public SectorGoogle · Reston, VA, USA; Washington D.C., DC, USA
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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: first seen 2 hours ago

Google median: 29 days open

The posting

This role may require travel up to 25% of the time.

In most instances, this position requires in-person interviews as part of the hiring process.

Must be a US Citizen to meet customer and compliance requirements, including potential access to classified information.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

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

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of software engineering experience in Python, Go, or C++, and experience with systems architecture.
  • Experience with LLM orchestration, embeddings, vector search, and agent frameworks.
  • Experience working in a cybersecurity domain (e.g., security engineering, threat detection and response, vulnerability research, or cyber operations) and with containerization and orchestration technologies (e.g., Docker, Kubernetes.).
  • Must possess an active Top Secret/SCI security clearance with current polygraph.

Preferred qualifications:

  • Experience acting as a forward-deployed engineer or technical consultant in mission environments.
  • Experience with Model Context Protocol servers, Representational State Transfer application programming interfaces, and Google AD or similar libraries.
  • Proven ability to interface directly with technical clients to scope and deliver software projects.

About the job

As an AI Engineering Software Engineer, you will design, build, and deploy Google AI solutions tailored for national security, public sector, and high-assurance enterprise missions. You will specialize in developing autonomous agentic systems, building custom test and evaluation harnesses, and implementing cybersecurity capabilities within air-gapped, sovereign, and disconnected cloud environments. In this role, you will embed directly with customer technical teams to size, architect, and deliver scalable mission solutions while serving as a versatile technical leader across the broader delivery portfolio.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Design and deploy autonomous agent frameworks using RAG, multi-agent coordination, and custom evaluation harnesses to monitor model accuracy and drift.
  • Productionize high-throughput AI integrations for threat intelligence, incident response, and zero-trust cybersecurity workflows.
  • Engineer air-gapped and sovereign cloud AI deployments adhering to strict defense and security compliance frameworks (e.g., FedRAMP High).
  • Optimize model execution, local caching, and containerized runtimes for restricted hardware and bare-metal environments.
  • Embed with technical stakeholders to translate mission needs into modular AI solutions and mentor teams on system sustainment.
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