Senior Product Manager, AI Data and Systems Platform
at Google
Location
San Jose, CA, USA; New York, NY, USA
Compensation
$192k–$278k USD
Type
full time
Posted
2 weeks ago
Market range · company + function + seniority
p25 · target · p75 · n=800
Posted $278k · in the market band
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Job description
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
As a Senior Product Manager on the AI Data and Systems team within People Operations (POps) Engineering, you will drive the upstream product strategy and long-term goals for Google’s internal "Customer Zero" transformation into an AI-native enterprise.
At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google’s IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Drive the upstream product strategy, multi-quarter goals, and roadmap for a horizontal AI platform pillar—such as multi-agent orchestration, enterprise people data products, or the agentic evaluation and developer experience lifecycle.
- Identify high-impact employee and developer problems across product areas, translating shared needs into reusable platform products, intuitive self-serve capabilities, and measurable portfolio return on investment (ROI).
- Partner with engineering and vertical product leaders to define clear product boundaries between horizontal platform capabilities and domain-specific applications, advocating a "build once, reuse everywhere" product philosophy.
- Collaborate with Data Science, Security, Privacy, and Legal partners to establish empirical product quality standards—replacing manual launch reviews with automated evaluation frameworks, auto-raters, and built-in safety guardrails.
- Lead cross-organizational product alignment with partner teams across Google (including Cloud and Core AI), guiding build-vs-buy product decisions that eliminate duplication and accelerate time-to-value.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in product management or a related technical role.
- 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.).
- Experience integrating generative AI tools or LLM interfaces into workflows.
- Experience managing AI/ML or generative AI products, including: agentic workflows, model optimization, and retrieval/evaluation frameworks.
Preferred qualifications:
- Master's degree in a technology or business related field.
- 5 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.
- Experience defining product roadmaps for APIs, SDKs, enterprise data products, or developer tooling.
- Experience partnering with Data Science, Privacy, Security, and Legal teams to establish empirical, automated product governance—using online/offline evaluation pipelines, auto-raters, latency/token budgets, and automated guardrails.
- Experience aligning executive product and engineering leaders across organizational boundaries, defining clear platform-versus-application boundaries, driving "build once, reuse everywhere" adoption, and evaluating build-versus-buy trade-offs.
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