Lead a team of Generative AI Forward Deployed Engineers (FDEs) at Google Cloud, bridging the gap between cutting-edge AI and production-grade customer solutions. This role involves hands-on coding, debugging, and co-deploying bespoke agentic solutions directly within client environments.

You will provide crucial technical mentorship, aligning with product, engineering, and sales leadership. Your primary focus is empowering your team to overcome production-level challenges, including data readiness, integration complexities, and state management, ensuring AI achieves enterprise-grade maturity.

Join an exciting Go-To-Market team driving the AI revolution. Leverage Google's deep AI portfolio, including Gemini models and Vertex AI, to solve business problems collaboratively with direct access to DeepMind's expertise. Be a catalyst for customer success and define the future of cloud computing.

Establish engineering excellence through code standards, architectural best practices, and performance benchmarks.

Collaborate with sales and technical leadership to define requirements for high-impact opportunities, deploying specialized AI/ML experts to key accounts.

Lead technical hiring for the FDE team, assessing AI/ML, systems engineering, and coding proficiencies to build a top-tier engineering unit.

Address skill gaps in emerging AI technologies, ensuring the team maintains cutting-edge subject matter expertise.

Partner with product and engineering teams to remove blockers and incorporate field insights into roadmaps, developing internal tools for enhanced organizational efficiency.

A Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent practical experience is required.

Possess at least 8 years of experience in cloud computing or customer-facing technical roles.

Have a minimum of 2 years of experience managing software engineering, FDE, or similar technical customer-facing teams within a cloud computing environment.

Demonstrate experience in developing AI/GenAI solutions, including the design of multi-agent workflows or Retrieval-Augmented Generation (RAG) systems.

Proficiency in Python or a comparable coding language is essential.