Senior Staff Forward Deployed Engineer, GenAI, Google Cloud

Requirements:

• 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.

Nice to Haves:

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Experience identifying business problems and translating hardware/AI constraints for C-suites and technical teams.
• Experience influencing and driving outcomes with cross-functional teams on engagements of high complexity and large scope and scale.
• Experience performing discovery interviews to identify business problems and translate hardware/AI constraints for C-suites and technical teams.
• Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

What You'll Be Doing:

• Serve 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 (ROI).
• Architect 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.
• 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.

Perks and Benefits:

• Exciting opportunity to work on cutting-edge AI products.
• Collaborative culture providing direct access to DeepMind's engineering and research minds.
• Opportunity to shape Google Cloud's future product roadmap.
• Equal opportunity and affirmative action employer commitment.