IT & Software

Staff Forward Deployed Engineer, Google Cloud

Google

London · Greater London · United Kingdom

Overview

In this role you will bridge frontier AI products with production-grade reality inside customer environments, shipping bespoke agentic solutions and embedding with strategic accounts. You’ll code the connective tissue between Google’s AI stack and live infrastructures, ensuring scalable, observable, and safe AI systems. You work with cross-functional teams to turn field insights into product improvements and drive enterprise adoption. This is a high-agency role with a founder’s mindset, offering impact across customers and Google’s AI portfolio.

Responsibilities
  • Bridge Google AI products with customer live environments and productionize agentic workflows
  • Code, debug, and ship bespoke agentic solutions within customer environments
  • Embed with strategic accounts to deploy high-quality AI systems (white-glove deployment)
  • Identify repeatable field patterns and convert them into reusable modules or feature requests
  • Co-build with customer teams to promote Google-grade development practices
  • Develop high-performance evaluation pipelines and observability frameworks for accuracy, safety, and latency
  • Synthesize field insights into Google Cloud product roadmap and influence future tooling
Key requirements
  • Bachelor’s degree in Engineering, Computer Science, or related field
  • 8 years of experience in cloud computing or technical customer-facing roles
  • Experience taking production-grade AI-driven solutions from conception to launch on cloud platforms (GCP)
  • Experience building pipelines for structured and unstructured data using vector databases and RAG-like architectures
  • Experience leading technical discovery sessions
  • Strong collaboration with cross-functional teams
  • High initiative and ownership mindset
  • Excellent communication and stakeholder management
  • Google Cloud Platform (GCP) / Vertex AI experience
  • Vector databases
  • Retrieval-Augmented Generation (RAG) architectures

Reference: WJ-747_31057099

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