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.
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.