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

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
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benefits at Google
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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.

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.