Product Manager, Central Products
Meta is hiring for the position of Product Manager, Central Products as a remote role open to applicants in United States. The listing describes it as a full-time, management position.
DGJ summary of this job
Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.
Meta is hiring for the position of Product Manager, Central Products as a remote role open to applicants in United States. The listing describes it as a full-time, management position.
From the advert, the main requirements are 10+ years of experience.
The employer does not state a salary in this listing; DGJ Insight below shows an official pay benchmark for the place where one exists.
Dev Global Jobs found this job on Jobicy on Nov 8, 2026.
- Employer
- Meta
- Location
- Remote (United States)
- Job type
- Full-time
- Level (from the title)
- management
- Pay
- Not stated by the employer
- Experience asked
- 10+ years
- Found
- Nov 8, 2026 on Jobicy
- Employer text
- 616 words, about 3 min to read
- Apply only on the official page (jobicy.com). Dev Global Jobs is not the employer and never asks for a fee.
- Compare your own experience with the 10+ years the advert asks for, and show it clearly near the top of your CV.
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DGJ Insight
Our own data about this role and place, from official statistics and our live job index.
Source: OECD Average annual wages, 2025
About the role
Full text from the employer, as published on Jobicy, arranged into sections. Nothing added or removed.
Meta Product Managers work with cross-functional teams of engineers, designers, data scientists, and researchers to build products. We are looking for extremely effective Product Managers to help innovate and execute product initiatives across the company, value moving quickly, and lead AI transformation at scale.
This job description represents different full-time roles across Meta.ResponsibilitiesIs the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals* Generate buy-in and drive consensus across organizations. Bring clarity and structure to ambiguous opportunities.
Consistently demonstrate initiative and execute with limited oversight Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis Translate AI capabilities into compelling, differentiated product visions that define market categories Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement Drive product development with teams of engineers and designers, while maintaining team health Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale Foster a culture of rapid experimentation and learning that becomes a competitive advantage Scale AI best practices (including responsible AI use), workflows, and artifacts across the organization so capability compounds exponentially Plan, initiate, and manage information technology projects for web-based products, applications, and platforms Orchestrate complex execution across multiple organizations by combining AI automation with strategic human oversight at scale Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm Use AI-enabled tools to build products-setting the standard for PM technical capability Interpret research and state-of-the-art learnings to design product strategy and apply rigorous logical reasoning at the frontier Demonstrate expert understanding of system/architecture trade-offs and how they impact user experience and business outcomes; lead strategic technical decisions with engineering leadership Integrate data, usability studies, research, and market analysis into product strategies and requirements to enhance user satisfaction and improve engineer productivity Express complex and technical concepts at the right altitude, choosing the right medium and level of detail for the audience (XFN partners, execs, engineering, etc.) Understand Meta's strategic and competitive position and deliver products that are aligned with our mission and recognized best in the industry Define and analyze metrics that inform the success of products.
Identify and track key performance metrics.
Drive decision-making through user insights, quantitative analysis, and AB testing Design sophisticated experiments and interpret results (leveraging AI) to drive strategic product decisions Define and run evaluations (evals) to interpret model outputs at scale-establishing evaluation as a strategic capability for AI-powered experiencesQualificationsDemonstrated proficiency using AI-enabled tools to build product artifacts at scale 10+ years of experience working collaboratively with engineering, design and user research teams 10+ years product management and/or Product Design Experience developing and championing AI-native strategies across organizations Critical thinking and analytical leadership experience Experience navigating through the full product life-cycle, integrating customer feedback into product requirements, driving prioritization, and pre- and post-launch execution Experience presenting to executive audiences BA/BS in Computer Science or related field Experience building 0-1 AI-native products, platform/ecosystem products, or marketplaces Experience in a consumer-focused technology company Track record of scaling AI best practices across organizations Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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