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NEXTMOVEFDE careers · United States
Google

Forward Deployed Engineer IV, Google Public Sector

AI summary of the role

Forward Deployed Engineer on Google Public Sector's FDE team, building production-grade agentic AI solutions for Federal and SLED customers.

What you’ll do

  • Develop production-grade agentic workflows (multi-agent systems, MCP servers) from prototypes to measurable ROI
  • Architect and code integrations between Google AI products and customer infrastructure (APIs, legacy data, security perimeters)
  • Build evaluation pipelines and observability frameworks for accuracy, safety, and latency
  • Identify field patterns and convert them into reusable modules or product feature requests

What you’ll bring

  • Bachelor's degree in Engineering, CS, or equivalent practical experience
  • 8 years of software development experience with Python or similar
  • 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) · Model Context Protocol (MCP) · LangGraph · CrewAI · ADK · Vertex AI Pipelines · Kubeflow · MLflow · BigQuery · VertexAI · RAG

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 As a part of the Google Public Sector Forward Deployed Engineering (GPS FDE) team, you will join squad of "innovator-builders" who rapidly deploy production-grade, secure AI solutions across Federal and SLED environments. You will operate with a high-agency startup mindset, where engineers don’t just advise; they actively code, debug, and co-build bespoke agentic workflows directly alongside customers. You will resolve complex integration, data sovereignty, and security challenges within strict compliance frameworks. You will help the GPS FDE team accelerate 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
More from the job description

About the job As a part of the Google Public Sector Forward Deployed Engineering (GPS FDE) team, you will join squad of "innovator-builders" who rapidly deploy production-grade, secure AI solutions across Federal and SLED environments. You will operate with a high-agency startup mindset, where engineers don’t just advise; they actively code, debug, and co-build bespoke agentic workflows directly alongside customers. You will resolve complex integration, data sovereignty, and security challenges within strict compliance frameworks. You will help the GPS FDE team accelerate 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 develop [... source excerpt omitted ...] i-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI). 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 ...] ata 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 complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). Proven experience architecting integrated systems, navigating real-time inference constraints, and implementing model quantization for re

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