Staff Forward Deployed Engineer, Google Cloud Public Sector

Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol 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.Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.Identify repeatable field patterns and technical “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 instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.Minimum qualifications, Bachelor’s degree in Engineering, Computer Science, a related field, or

equivalent practical experience, 8 years of experience with software development using Python or similar coding languages.Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (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.Active, or the ability to obtain, a Security Check (SC) UK security clearance.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, or Google’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.Experience in a post-sales or technical consulting delivery function.Knowledge of large language model native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.As an AI Forward Deployed Engineer (FDE) at Google Cloud, you will be the technical engine of our Innovation team, working directly with highly regulated clients to help them transform their operations using advanced AI/ML technologies. You are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as a “builder-consultant,” moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.In this role, you will address blocker to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you will serve a dual purpose: providing “white glove” deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Must be a British citizen to meet compliance and security clearance requirements.In most instances, this position requires in-person interviews as part of the hiring process.Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.8 years of experience with software development using Python or similar coding languages.Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (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.Active, or the ability to obtain, a Security Check (SC) UK security clearance.