{"id":1277875,"url":"https://alion.io/job/google-forward-deployed-engineer-iv-genai-public-sector","title":"Forward Deployed Engineer IV, GenAI, Public Sector","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":114,"ghost_share":0,"stale_share":0.982,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Reston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":135000,"max_usd":265000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":914},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"GCP","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"BigQuery","optional":true},{"name":"CI/CD","optional":true},{"name":"CrewAI","optional":true},{"name":"Google ADK","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Kubeflow","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LLM","optional":true},{"name":"MLFlow","optional":true},{"name":"Quantization","optional":true},{"name":"Vertex AI","optional":true}],"status":"closed","first_seen_at":"2026-09-15T16:38:53Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-16T18:13:57Z","board_verified":false,"closed_at":"2026-10-16T18:13:57Z","days_open":31,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":31},"description":"About the job\nThe 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.\nGoogle 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.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nServe as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.\nArchitect 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.\nBuild high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.\nIdentify 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.\nCo-build with Customer Engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.\nQualifications\nMinimum qualifications:\nBachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.\n8 years of experience with software development using Python or similar coding languages.\nExperience architecting AI systems on cloud platforms (e.g. Google Cloud Platform (GCP)).\nExperience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.\nExperience leading technical discovery sessions with customers.\nPreferred 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