Forward Deployed Engineer IV, GenAI, Public Sector
AI summary of the role
This role is a forward deployed engineer on Google Public Sector's team, building production-grade AI solutions for federal and SLED customers.
What you’ll do
- Develop complex AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers).
- Architect and code integrations between Google AI products and customer infrastructure, including APIs, legacy data silos, and security perimeters.
- Build evaluation pipelines and observability frameworks for agentic systems to meet accuracy, safety, and latency requirements.
- Identify repeatable field patterns and convert them into reusable modules or product feature requests.
What you’ll bring
- Bachelor's degree in Engineering, Computer Science, or equivalent practical experience.
- 8 years of software development experience using Python or similar languages.
- Experience architecting AI systems on cloud platforms (e.g., GCP).
- Experience building pipelines for structured/unstructured data using vector databases and RAG architectures.
Technologies
Python · Google Cloud Platform (GCP) · vector databases · RAG · LangGraph · CrewAI · ADK · Vertex AI Pipelines · Kubeflow · MLflow · BigQuery · VertexAI
About Google
Builds global consumer, ads, cloud, developer and AI platforms spanning Search, YouTube, Android, Workspace and Gemini.
Public
Source and classification
Production engineering · Evidence for this classification:
About the job The Google Public Sector Forward Deployed Engineering (GPS FDE) team is a squad of direct "innovator-builders" who rapidly deploy production-grade, secure AI solutions across Federal and SLED environments. Operating with a high-agency startup mindset, our engineers don’t just advise; they actively code, debug, and co-build bespoke agentic workflows directly alongside our customers. We resolve complex integration, data sovereignty, and security challenges within strict compliance frameworks. Ultimately, the GPS FDE team accelerates the safe, reliable adoption of generative AI across mission-critical operations while feeding field insights directly back to Google Cloud Product engineering. 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
More from the job description
About the job The Google Public Sector Forward Deployed Engineering (GPS FDE) team is a squad of direct "innovator-builders" who rapidly deploy production-grade, secure AI solutions across Federal and SLED environments. Operating with a high-agency startup mindset, our engineers don’t just advise; they actively code, debug, and co-build bespoke agentic workflows directly alongside our customers. We resolve complex integration, data sovereignty, and security challenges within strict compliance frameworks. Ultimately, the GPS FDE team accelerates the safe, reliable adoption of generative AI across mission-critical operations while feeding field insights directly back to Google Cloud Product engineering. 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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Serve as a developer for complex AI applica [... source excerpt omitted ...] , multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment. Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team. Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency. Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Co-build with Customer Engineering teams to insti [... source excerpt omitted ...] for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. 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 complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Proven experience architecting integrated systems, navigating real-time inference constraints, and implementing model quantization for resource-constrained environments. Proficiency in Vertex AI Pipelines, Kubeflow, or
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