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).
Build high-performance evaluation pipelines and observability frameworks to ensure partner developed agentic systems meet requirements for accuracy, safety, and latency.
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.
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.
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.
Minimum qualifications
Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
8 years of experience in cloud computing or a technical customer-facing role.
2 years of experience managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment.
Experience developing AI/Generative AI (GenAI) solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems.
Preferred qualifications
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.
Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
8 years of experience in cloud computing or a technical customer-facing role.
2 years of experience managing a software engineering, forward deployed engineering, or a similar technical customer-facing team in a cloud computing environment.
Experience developing AI/Generative AI (GenAI) solutions utilizing AI tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems.
