Technical Program Manager III, Software Development, Cloud AI Systems

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
  
• 5 years of experience in program management.
  
• Experience in cloud computing emerging technologies or related technical fields.
• Experience in software program management or engineering management.

Preferred qualifications:

• 5 years of experience managing cross-functional and cross-team projects.
• Experience partnering with engineering, product management and support teams to facilitate the design and delivery of cloud programs.
  
• Experience with technologies such as virtualization and complex software infrastructure systems, compute, storage, data migration, capacity, load balancing, and software defined networking.
  
• Experience managing execution of complex programs that span multiple engineering teams through the software project lifecycle (build, test, and release on time).
  
• Experience in communicating technical concepts to non-technical audiences.

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 engineers.

As a Technical Program Manager for MSCA, you will help deliver a variety of programs in the area of data center software. You will be responsible for the development of software to support new Google-designed hardware products, including software for planning the deployment of the new hardware to our data centers, monitoring the hardware, detecting and diagnosing failures in the hardware, and scheduling repairs.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $156,000-$229,000 + 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:

• Scope, plan, and manage large programs, including management of associated financial and human resources, quality of software development and features, risks, schedules, communication plans, and deliverables.
  
• Provide management with forecasts of project deliverables and detailed status updates.
  
• Present your team's analyses, recommendations, and approaches to stakeholders and executive management.
  
• Initiate new software development programs, identify and deliver software features that drive performance, scale, functionality, security, quality, and efficiency, based on prioritized needs.
•  Be the catalyst for program support and delivery.