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 such as Google Cloud Platform.
• Experience building pipelines for structured and unstructured data using vector databases and Retrieval-Augmented Generation (RAG)-like architectures for 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-suite and technical teams.
• Experience influencing cross-functional teams and driving outcomes on large, complex engagements.
• Experience performing discovery interviews for business problem identification and constraints translation.
• Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and optimization techniques for state management and granular tracing.

What you'll be doing

• Develop complex AI applications, transitioning prototypes to production-grade agentic workflows like multi-agent systems and Model Context Protocol servers that drive measurable ROI.
• Architect and code integrations between Google AI products and customers' live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation pipelines and observability frameworks to ensure accuracy, safety, and latency compliance of agentic systems.
• Identify repeatable field patterns and friction points in Google's AI stack to create reusable modules or product feature requests for engineering teams.
• Collaborate with customer engineering teams to implement Google-level development best practices for long-term project success and adoption.

Perks and benefits

• Opportunity to work with Google's most advanced AI portfolio, including frontier Gemini models and the full Vertex AI platform.
• Collaborative culture with direct access to DeepMind’s engineering and research teams.
• Role designed for high-agency engineers with a founder’s mindset, providing significant impact on AI production in enterprise environments.
• Chance to shape Google Cloud’s future AI product roadmap through embedded customer engagement and real-world feedback.