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

Google•Washington, DC

3d•$174,000 - $252,000

About The Position

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. 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 Google solutions to government and education, helping United States public sector institutions accelerate digital transformations and addressing the needs of local, state, and federal government and educational institutions.

Requirements

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, such as security engineering, threat detection and response, vulnerability research, or cyber operations, and with containerization and orchestration technologies, such as Docker and Kubernetes.
Must possess an active Top Secret/SCI security clearance with current polygraph.

Nice To Haves

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, such as 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.