Job Description

Minimum qualifications

• Bachelor's degree in a technical field, or equivalent practical experience.
• 5 years of experience in project management on technical and cross-functional projects within software engineering organizations.
• Experience managing end-to-end software engineering programs.

Preferred qualifications

• Experience with driving AI product development.
• Experience with AI first software development cycle.
• Experience in software development, testing, and deployment process.

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.

Google Pay India is looking for an experienced Technical Program Manager in Singapore to lead complex, high-impact consumer product programs across our Consumer App and Growth charter driving user acquisition, activation, engagement, and core app experiences for hundreds of millions of users.

In this role, you will partner closely with product management, engineering, UX, data science, marketing, and legal/privacy across global hubs to turn ambiguous consumer growth opportunities into high-velocity experiments and scaled product launches. We are looking for a strong consumer product program leader who thrives in ambiguity, brings sharp technical and product judgment, and advocates AI-Driven Development (DevAI) embedding agentic workflows across both the product development lifecycle (AI-assisted specs, prototyping, and automated eval/test loops) and program management to accelerate team velocity, risk mitigation, and funnel impact.

Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses.

In this role, you will partner closely with product management, engineering, UX, data science, marketing, and legal/privacy across global hubs to turn ambiguous consumer growth opportunities into high-velocity experiments and scaled product launches. We are looking for a strong consumer product program leader who thrives in ambiguity, brings sharp technical and product judgment, and advocates AI-Driven Development (DevAI) embedding agentic workflows across both the product development lifecycle (AI-assisted specs, prototyping, and automated eval/test loops) and program management to accelerate team velocity, risk mitigation, and funnel impact.

Responsibilities

• Lead end-to-end consumer product program management across Google Pay India consumer and growth portfolio, driving user acquisition, activation, engagement, and new consumer experiences for hundreds of millions of users.
• Drive high-velocity consumer product and experimentation execution, managing cross-functional dependencies across mobile client, backend services, ML/personalization, and UX.
• Advocate AI-Driven Development (DevAI) and agentic workflows across both the product SDLC and program management partnering with engineering, program manager, and UX to embed AI-assisted specs, automated eval/testing loops, and rapid prototyping into sprint execution, while building agentic tooling that automates routine operations, experiment governance, and predictive risk mitigation.
• Exercise strong technical and product judgment to understand engineering challenges, contribute to architecture and UX design discussions, evaluate trade-offs across client performance, latency, and platform reuse, and guide technical decisions.