Minimum qualifications:
- Bachelor's degree in a 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 complex cross-functional or cross-team projects.
About the job
In a Delivery Technical Program Manager role within Google’s Applied AI team, you serve as the operational glue of the deployment pod, driving the startup-like velocity required to move enterprise customers from pilot phases to full-scale production. Partnering closely with the technical Directly Responsible Individual (DRI), you provide the project management oversight needed to translate complex technical builds into high-impact business solutions.
Furthermore, you collaborate with the Leadership team to establish a transparent program management state for every account. In this structure, you are the definitive center point for all customer reviews, ensuring a unified voice between the customer’s business goals and Google’s development output. You will develop a standardized Customer Health Hub where every account’s state including Resolution Rate, Latency (TTFT), and Eval Scores is surfaced in real-time. You will lead these reviews with leadership to ensure global consistency across the portfolio. You will conduct weekly audits to evaluate the technical friction and stakeholder complexity of each account to ensure no critical deployment hits a bottleneck. Additionally, you will act as the hub connecting all the stakeholders (Solution Architecture, Agent Development, and Product) to ensure that technical DRIs remain focused on building while TPMs drive the roadmap, risk mitigation, and executive reporting.
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.
For United States Applicants:
The US base salary range for this full-time position is $240,000-$334,000 + 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
For Canada Applicants:
The Canada base salary range for this full-time position is CAD 248,000-254,000 + 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 eval 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.
