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.

The Developer AI team in Google Core is transforming the way software development is carried out at Google. We are bringing new capabilities based on the latest AI research to Googler developers, and leading the tech industry’s evolution of how software is built. Our goal is to make it easy for all developers to improve the world by creating fast, high-quality, and trustworthy experiences with the best technology from Google and the open source ecosystem.

In this role, you will support critical programs in the Developer AI portfolio. You will help operationalize the roadmap for AI-powered features. You will partner closely with the TPM, Product, and Engineering to facilitate the delivery of advanced AI capabilities, ensuring execution alignment and operational efficiency across these key technical verticals.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

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

• Support the end-to-end delivery of initiatives within the vertical, specifically focused on models and serving infrastructure.

• Partner with cross-functional teams to facilitate execution for key internal products, ensuring alignment with broader engineering goals.

• Drive roadmap planning and dependency management, coordinating across model development, back-end infrastructure, and serving teams.

• Establish and maintain operational feedback loops to measure program health, iterating based on performance data for model-serving and knowledge-retrieval systems.

• Manage stakeholder communication and reporting for multiple verticals, ensuring clarity and alignment across the core developer organization and partner teams.

Minimum qualifications

• Bachelor's degree in a technical field, or equivalent practical experience.

• 5 years of experience in program management.

• Experience in a technical engineering role (e.g., software engineer, machine learning engineer, research software engineer, infrastructure engineer, etc.).

• Experience leading or contributing to generative AI programs (e.g., Large Language Models (LLMs), model serving infrastructure, or AI-powered software features).

Preferred qualifications

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

• Experience launching consumer or enterprise-grade artificial intelligence/maching learning products.

• Experience developing or scaling developer productivity tools to improve the software development lifecycle (SDLC).

• Experience with machine learning operations or DevOps practices, including the management of automated CI/CD pipelines.