Engineering Manager, Applied AI, Cloud Support Intelligence

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• Experience in technical leadership, leading project teams, and setting technical direction.
• Experience in people management.

Preferred qualifications:

• Master's degree or PhD in related field.

About the job

Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.

Google Cloud is experiencing rapid growth, and scaling traditional support linearly is no longer sustainable. The Cloud Support Platform (CSP) Intelligence team is supporting Google Cloud’s transformation into an AI-first, agentic support ecosystem across Google Cloud Platform (GCP), Google Workspace (GWS), Billing, and Cloud Helpdesk.
Our mission is to deliver frictionless, agentic support at scale—turning every customer interaction into instant, zero-touch resolution or elevated human-steered troubleshooting, while continuously feeding insights back to self-heal Google Cloud products. We build and operate the core AI Layer powering Google Cloud Support: multi-agent self-service agents , ubiquitous headless intake agents embedded directly into developer workflows (Cloud Console, IDEs, Slack), stateful human-in-the-loop AI Agents, and continuous learning pipelines backed by rigorous automated evaluation.
Joining CSP Intelligence means leading at the frontier of applied enterprise GenAI—solving complex multi-agent orchestration, high-reliability (99.99%) distributed systems, and real-time reasoning challenges that directly impact millions of Google Cloud developers, enterprise administrators, and support engineers worldwide.
Our work is measured in outcomes the business feels directly — deflection rate, time-to-resolution, average handle time, and customer effort.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

Responsibilities

• Lead, grow, and develop a team of engineers building production AI agent systems for Google Cloud Support, owning delivery, technical direction, and career growth for the team.
• Own a significant problem area within the CSP Intelligence charter
• Set technical direction for multi-agent architecture, orchestration, tool/skill design, and evaluation in an area where the platform landscape is still being decided — and make the calls on what we build, what we adopt, and what we retire.
• Drive measurable business outcomes: self-service deflection rate, time-to-resolution, average handle time, and customer effort score — and define the metrics and evaluation harnesses that prove it.
• Build the quality bar for applied AI: systematic evals, regression gates, and safe rollout practices for agents that take real actions on customer accounts.