Software Engineer, Rapid Innovation, Google Public Sector

Job description

Act as a trusted advisor to customers by understanding their business process and objectives. Design and build genAI-driven solutions spanning AI, data, and infrastructure. Demonstrate how Google Cloud is differentiated by working with customers on application prototypes; demonstrating generative AI features; prompting and tuning models; and optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues in generative AI applications. Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable customers and internal teams. Work with peers to include the full cloud stack into overall architecture. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements. Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement. Travel as needed. Minimum Qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. 5 years of experience with software development using Python or similar coding languages. Experience architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and (retrieval-augmented generation) RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Must possess an active Top Secret/SCI security clearance with current polygraph. Preferred Qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation). Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.