Partner Forward Deployed Engineering Manager Iii, Genai, Google Cloud

Google Google · Big Tech · Singapore

Manager of a GenAI Forward Deployed Engineering (FDE) team responsible for bridging the gap between frontier AI products and production-grade reality within partners. This role involves coding, debugging, and jointly shipping bespoke and scalable agentic solutions with partners, addressing integration complexities, data readiness, and state-management issues. The role also focuses on building evaluation pipelines and observability frameworks, identifying patterns for product roadmap input, and co-building with partner FDE teams to instill best practices.

What you'd actually do

  1. Serve as a team lead and developer within the Google Cloud partner FDE organization to drive the transition from rapid prototypes to production-grade, replicable agentic workflows (multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).
  2. Build high-performance evaluation pipelines and observability frameworks to ensure partner developed agentic systems meet requirements for accuracy, safety, and latency.
  3. Identify repeatable partner and field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
  4. Co-build with a strategic AI partner’s own Forward Deployed Engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
  5. Help partners to build their own agentic delivery capabilities to set them up for long-term success, focusing on the ROI at customer engagements ensuring customer activation.

Skills

Required

  • Experience developing AI/Generative AI (GenAI) solutions utilizing AI tools
  • Designing multi-agent workflows
  • Retrieval-Augmented Generation (RAG) systems
  • cloud computing
  • technical customer-facing role
  • managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment

Nice to have

  • Master’s degree or PhD in AI, Computer Science, or a related technical field.
  • Expertise in designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
  • Ability to design end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection), state management, and tool-calling protocols.
  • Ability to perform deep discovery interviews to find the true business problem and translate complex hardware/AI constraints for C-suites and deep-technical teams.
  • Background in architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance.

What the JD emphasized

  • production-grade reality
  • code, debug, and jointly ship bespoke and scalable agentic solutions
  • address blockers to production
  • integration complexities
  • data readiness issues
  • state-management issues
  • agent engineer bridging the gap between AI prototypes and production-grade reality
  • production-grade, replicable agentic workflows
  • agentic systems meet requirements for accuracy, safety, and latency
  • agentic delivery capabilities

Other signals

  • building bespoke and scalable agentic solutions
  • addressing blockers to production
  • transforming real-world field and partner insights into Google Cloud’s future product roadmap
  • leading the AI revolution for businesses worldwide