Staff Forward Deployed Engineer, Google Cloud

Google
London, UK
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

LangGraph Framework Application Programming Interfaces (APIs) Artificial Intelligence Cloud Computing Software Debugging High-Level Architecture Unstructured Data Google Cloud ReactJS Evaluation Pipelines Large Language Models Multi-Agent Systems
+8 more
Generative AI Information Technology CrewAI Machine Learning Operations Google Gemini Model Context Protocol DeepMind Data Pipelines

Job description

As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. You will function as an ā€œinnovator-builder,ā€ moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. Your role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity, by embedding with strategic accounts, you will serve a dual purpose: providing ā€œwhite gloveā€ deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It’s an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google’s brand credibility-a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world’s most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind’s engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.

Responsibilities

  • Serve as a developer for 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 (ROI).
  • Architect and code the ā€œconnective tissueā€ 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 instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

Requirements

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.

  • 8 years of experience in cloud computing or a technical customer-facing role.
  • 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., * Master’s degree or PhD in Artificial Intelligence, Computer Science, or a related technical field.
  • Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, Agent Development Kit (ADK)) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
  • Knowledge of ā€œLLM-nativeā€ metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

About the company

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle’s EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC_KnowYourRights_10_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

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