Senior Manager, Training and Quality

Reed Technology•Dayton, OH

2d•$112,400 - $263,800

About The Position

The Senior Manager, Training & Quality leads two functions at the core of how Global Editorial Operations produces trusted content: the training that builds editorial capability, and the quality assurance that safeguards accuracy at scale. This role owns the strategy and leads the teams that design and deliver role-based learning and that govern editorial quality, modernizing both for an environment where AI is increasingly central to how content is created, delivered, and assured. This is a role for a builder who will lead the evolution of both functions toward an AI-first operating model, introducing AI into how training is delivered and how quality is measured while raising the bar on instructional design, assessment, and audit. The role involves simplifying and standardizing team operations, strengthening the durability of materials and know-how, and shaping the future roles and capabilities of these functions. Success means moving both functions beyond measuring activity toward demonstrating impact, connecting training effectiveness and editorial quality to on-the-job performance, content accuracy, and customer outcomes. The leader will manage a globally distributed team through meaningful change and partner closely with editorial leaders and analytics partners to ground decisions in clear, credible data. The Global Editorial Operations (GEO) organization is responsible for producing, managing, and delivering the content that powers LexisNexis products and customer experiences, with over 600 employees worldwide. GEO sits at the intersection of editorial excellence and technology, transforming premium legal and news content into trusted, scalable solutions for today’s legal landscape.

Requirements

5+ years leading L&D, training and/or quality functions, including managing people
A track record of driving change or transformation at scale in a complex, distributed organization
Experience building measurement systems and translating them into dashboards/reports that tie training and quality to operational and customer outcomes, ideally with hands-on fluency in tools such as Tableau, Power BI, Looker
Proven experience deploying AI in training and/or quality at scale, such as embedding AI into team workflows, not just personal use, and with the judgment to know where it helps, where it needs guardrails, and how to lead a team through adoption responsibly
A clear communicator who can present progress, risks, and tradeoffs to senior stakeholder
Experience with Learning Management Systems and Quality Assurance tools.
Grounding in instructional design and/or QA methods (adult-learning principles, sampling, calibration, error taxonomies) preferred

Responsibilities

Lead the redesign of a training operating model from predominantly manual, instructor-led delivery toward scalable, AI-enabled learning; de-risk single-point-of-failure roles by externalizing siloed knowledge into documented, AI-ingestible assets.
Lead the redesign of the editorial Quality Management System: QA frameworks, sampling, scoring standards, calibration, and feedback loops, optimizing for AI-assisted quality auditing (automated sampling, error detection, trend analysis, workflow monitoring) using defensible methods: rubrics, thresholds, and error taxonomies.
Build measurement systems that move beyond activity and satisfaction toward application and business outcomes, linking training effectiveness and editorial quality to downstream customer and business results.
Partner with the Content Performance Analyst to measure and track time-to-proficiency, post-training quality and accuracy, and AI-assisted versus unassisted performance.
Build strong relationships with editorial leadership, cross-functional partners (Technology, Finance, Metrics), and vendors; communicate strategy, progress, and risk to senior leadership through structured reporting.
Set short- and long-term goals, performance targets, and operating plans, including learning-effectiveness and quality-maturity targets.
Stay market-savvy, maintaining strong awareness of emerging AI training and QA trends; bring those insights into driving roadmap planning and content differentiation.