Senior Technical Program Manager II, Customer Engagement, Applied AI

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 10 years of experience in program management.
• Experience working with AI agents and GenAI-native architectures.
• Experience leading customer interactions.
• Experience building out technical roadmaps.

Preferred qualifications:

• 10 years of experience managing cross-functional or cross-team projects.

Experience building out technical roadmaps.

About the job

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with developers.

The Google Cloud Applied AI (AAI) Solutions Consulting team functions as a high-stakes unit responsible for Google’s most strategic AI deployments. We bridge the gap between experimental AI and enterprise reality, acting as the technical and strategic engine that turns complex business problems into production-ready agentic solutions.

As a Technical Program Manager you are the primary delivery Directly Responsible Individual (DRI) across multiple customers, and the orchestrator of delivery pods that span Product, Development, GTM, Partner and Customer teams. You are the operational glue for agentic AI deployments, managing daily execution and cross-functional dependencies, and driving the startup-like velocity required to move enterprise customers from pilot phases to full-scale production. You will lead direct customer interactions to define agent behaviors, ensuring the technical roadmap is anchored, while providing the strategic advisory necessary to navigate the transition from legacy stacks to GenAI-native architectures. Partnering closely with the technical DRI, you provide the project management oversight needed to translate complex technical builds into high-impact business solutions.

Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.

The Canada base salary range for this full-time position is CAD 240,000-246,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Please note that the compensation details listed in Canada role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Be a highly credible thought leader within Google and industry on the subject matter domain of the respective organization.
  
• Establish a reliable and visible cadence for portfolio reviews, decision making, prioritization, and resource management, whereby improvements are measurable and the impact can be felt organization wide.
  
• Lead the implementation of evaluate pipelines and testing frameworks, ensuring every Large Language Model (LLM) prompt or reasoning update is validated against golden datasets to prevent regressions in agent accuracy, persona alignment, and brand voice.
  
• Utilize specialized dashboards to monitor agent health, tracking Key Performance Indicators (KPIs) such as accuracy, hallucination rates, and latency to ensure the agent is production ready and provides a fluid, human-like experience.