Senior Technical Program Manager, Workspace Editors, Gen AI at Google

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8 years of experience in program management.
• Experience in integrations between first-party (in-house) and third-party technologies (API, off-line, etc.).

Preferred qualifications:

• 7 years of experience managing and driving developers projects (determine, gather, and analyze metrics for your projects and our systems).

• Experience in business intelligence platform, scripting or apps script.

• Experience working directly with Enterprise customers.

• Experience managing day-to-day execution of AI programs, launching app products in the market, and developing products with an understanding of current AI technologies and services.

• Experience working in a startup environment, and the ability to manage ambiguity, work self-sustaining, multi-task, and define successful approaches.

About the job

Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers.

Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.

The Editors Technical Program Manager (TPgM) team is a part of the Workspace organization, focusing on high-impact projects that are complex and urgent. We operate under principles of simplicity and adaptability, ensuring that our processes are levers to make work easier rather than additional toil. Our team is deployed across sites and we partner with Engineering, Product and UX functions to execute the direction of the Workspace suite.

AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google Deep Mind), work with exceptional leaders, and have the ability to impact billions of users across the world.

The US base salary range for this full-time position is $192,000-$278,000 + 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.

Responsibilities

• Understand complexities of building AI powered features for new and scaled products. Launch and land key AI capabilities and features for Workspace. Develop and drive strategies for ambiguous programs.
• Establish and optimize strategies, workflows, and best practices across the organization to drive operational excellence and team velocity.
• Monitor the balance between process excellence and unnecessary overhead to enable high velocity without compromising quality. Identify and implement risk mitigations, resolving issues by raising and managing appropriate escalations to break logjams.
• Act as a communication leader, proactively raising awareness to key stakeholders and executive audiences to avoid surprises. Leverage AI/ML tools and technical data to improve velocity, impact, and influence technical decision-making.
• Manage end-to-end project lifecycles for high-priority initiatives, from requirement gathering to feature prioritization. Decompose large-scale challenges into actionable workstreams and assign ownership.