Lead a team of AI/ML engineers focused on deploying cutting-edge Artificial Intelligence (AI) products into customer environments.

This role involves hands-on coding, debugging, and co-deploying bespoke agentic solutions within client infrastructures. You will provide deep technical mentorship, balancing strategic alignment with Product, Engineering, and Google Cloud Sales leadership. Your team will tackle production-level obstacles, including data readiness, integration challenges, and state management, to ensure AI achieves enterprise-grade maturity.

Join Google Cloud's Go-To-Market team and spearhead the AI revolution for businesses globally. Leverage Google's innovation legacy and advanced AI portfolio, including Gemini models and the Vertex AI platform, to solve complex business problems. Collaborate with DeepMind's engineering and research talent to drive customer success and shape the future of cloud computing.

Establish technical leadership by defining code standards, architectural best practices, and benchmarks to enhance team engineering excellence.

Collaborate with Sales and Tech Leadership to outline requirements for significant opportunities, deploying specialized experts to key accounts. Lead technical hiring for Forward Deployed Engineers, assessing AI/ML, systems engineering, and coding proficiency.

Identify critical skill gaps in emerging technologies like Model Context Protocol (MCP) and foundation models, ensuring continuous subject matter expertise. Work with Product and Engineering to remove impediments and integrate field insights into roadmaps, developing internal tools for greater organizational efficiency.

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

Possess 8 years of experience in cloud computing or a customer-facing technical role. This includes 5 years of experience managing software engineering, FDE, or similar technical customer-facing teams in cloud environments. Proficiency in Python or a comparable coding language is essential.

Demonstrated experience in developing AI/GenAI solutions, utilizing AI tools, or designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems is necessary. Preferred qualifications include a Master’s or PhD in AI, Computer Science, or a related technical field, along with experience in designing secure, observable multi-agent systems and working with manufacturing and conglomerate customers.