Staff Localization Program Manager

LinkedIn•New York, NY

17h•$115,000 - $186,000•Hybrid

About The Position

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of the 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.

Requirements

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

Nice To Haves

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

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