Staff Localization Program Manager

Job description

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role is based in New York, Sunnyvale, San Francisco, or Mountain View The Knowledge Management Solutions (KMS) team at LinkedIn is responsible for creating and delivering self-service content for LinkedIn’s members, customers and employees. The team creates instructional, procedural, and technical content using both traditional and AI-powered methods. This content is made available externally through LinkedIn's help centers, virtual chat assistants, and in-product experiences (including those powered by AI/GAI). Employees also use this content internally through enterprise search systems and CRMs. We are looking for a Staff Localization Program Manager to lead the strategy, systems, and execution required to scale AI-enabled localization at LinkedIn. This role is focused on owning AI-first localization workflows, platform integrations, and quality processes that improve translation quality, speed, and cost efficiency across global content experiences. The person in this role will serve as the subject matter expert for localization and the design of AI-native localization systems and workflows, partnering closely with Marketing Technology, Engineering, Data Science, and content teams to build scalable, production-ready solutions. Why Join Us? Play a foundational role in scaling AI-first localization from pilots to production Lead the design and program management of AI-powered localization systems across translation, evaluation, and quality validation, driving programs from concept through implementation. Lead high-impact work across content platform transformation and real-time AI first localization programs Deliver measurable business impact through faster delivery, stronger quality, and lower long-term localization costs Responsibilities: Advance LinkedIn’s localization maturity by scaling LLM-driven capabilities across global content Own the architecture and evolution of AI-enabled localization agentic systems, workflows, and operating models across the content ecosystem Lead the design and scaling of end-to-end localization capabilities across platform integrations, content routing, translation, evaluation, and quality validation. Drive the development of agentic and automated approaches that improve localization efficiency, consistency, and scalability across languages and content types. Partner with Data Science, Engineering, and content teams to deliver localization requirements across platform and AI initiatives Own localization performance targets and success metrics across automation, quality, speed, cost efficiency, coverage, and adoption, using data to track progress and guide prioritization. Improve translation quality and time to market while reducing long-term dependency on manual and vendor-heavy workflows Serve as the go-to expert for localization strategy, AI-enabled workflows, and system-level scale Basic Qualifications 8+ years of experience in localization, internationalization, language technology, AI-enabled content systems, or related program leadership roles 5+ years of demonstrated success leading complex, ambiguous, cross-functional programs as a senior individual contributor in a fast-moving environment. 5+ years of hands-on experience with translation management systems, machine translation, LLMs, NLP-based localization workflows, and AI-powered content operations 3+ years of demonstrated success building scalable localization and AI-enabled language systems, including automated quality evaluation frameworks and model-based approaches that improve end-user experiences. Professional working proficiency in English and at least one additional language, with 3+ years of experience applying both languages in a localization, content, translation, or multilingual business environment. 3+ years of experience using dashboards, SQL, or performance data to guide decisions Preferred Qualifications 2+ years of experience managing budgets, vendor relationships, and operational performance in a localization environment Strong understanding of content and localization systems, including CCMS, TMS, taxonomy, terminology, and metadata structures Experience building processes that increase efficiency and quality for teams at scale Experience with multilingual quality frameworks such as MQM, QE, and other structured quality evaluation approaches Experience managing terminology, glossaries, and style guides to ensure consistency across multilingual content and various translation types Experience supporting platform migrations, system integrations, or large-scale content transformations Strong communication and influencing skills, with the ability to lead through partnership across teams Suggested Skills Localization Operations & Strategy AI/ML in Localization & Content Systems Technical Program Management Data Analysis & Quality Management Process Design & Scalability Change Management & Adoption Vendor & Budget Management LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $115,000 to $186,000 Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit . Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. 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