Jobs at Pluralsight

Manage a portfolio of enterprise customers to drive adoption, retention, renewals and expansion. Own lifecycle from onboarding to renewal, use data and internal tools to measure health and utilization, take corrective actions, forecast risk and growth, and build trusted advisor relationships with senior technology leaders.

Lead design, launch, and lifecycle management of Pluralsight solutions (AI, Cloud, Security). Define expert POV, build curricula, labs, assessments, and blended learning programs. Own roadmap, metrics, GTM partnership with Sales and Marketing, and continuous iteration using data and SME collaboration to drive enterprise customer outcomes.

Lead and scale Implementation & Adoption services to drive time-to-value, adoption depth, and renewals. Own delivery model, playbooks, scalability, team growth, executive escalations, cross-functional partnership with Sales/CS/Product/Finance, services innovation, and KPI reporting (time-to-value, go-live rate, adoption, CSAT, retention).

Source, recruit, and vet external content creators (authors) across technical domains. Conduct screening calls, manage candidate pipelines, coordinate auditions and onboarding tasks, maintain candidate records and CRM data, and collaborate with curriculum and enablement teams to refine outreach and qualification processes.

Guide customers through fast-paced SaaS onboarding: run kickoff and enablement sessions, configure platform settings, train admins/managers/learners, track progress across multiple projects, coordinate with Sales/Customer Success/Support, and drive customer launch and adoption.

Own and evolve Pluralsight's Cloud and Security learning solutions by defining strategy, roadmaps, curricula, and KPIs. Partner cross-functionally to design blended programs (courses, labs, assessments, instructor-led training), support sales, monitor market trends, and iterate product offerings using data and customer feedback to drive adoption, pipeline, and measurable business outcomes.

Manage an enterprise portfolio end-to-end to drive adoption, retention, renewals, and expansion. Use customer health and utilization data to forecast risk, recommend corrective actions, and enable customers to realize value. Build executive relationships, guide implementations and learning strategies, and collaborate with sales to meet gross and net retention goals.

Lead company-wide data governance and standards, enforce data contracts and schema/version control, manage PII/RBAC and master data, establish data-quality metrics and monitoring, grow and run the governance team, remain hands-on with data profiling and SQL, and use AI to accelerate governance work and modeling.

Lead architecture, build, and operate customer-facing analytics platform: design ELT and metric governance, implement low-latency serving (OLAP), ensure reliability/performance, mentor engineers, partner with product, and use AI coding tools to accelerate development.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

Lead and grow a marketing operations team to own martech, lead management, campaign attribution, and GTM data architecture. Govern vendor lifecycle, design and maintain lead/campaign data flows, ensure CRM sync and data quality, and partner cross-functionally with Revenue Ops, Analytics, and IT to drive reliable reporting and platform transformations.

Design and manage assessment blueprints and items end-to-end, apply psychometric rigor (equating, calibration, reliability/validity), run item/test analyses, lead vendor/SME collaboration, maintain standards and QA, and own documentation and continuous improvement of the assessment portfolio.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

The AI Solutions Delivery Architect will design and implement AI-based solutions, aligning with business strategies to optimize transformation. This role includes evaluating AI platforms, leading AI deployments, and ensuring effective adoption strategies across teams.

Lead Pluralsight's curriculum strategy to identify and shape future skills; translate market and technology trends into a curriculum roadmap; align with product, GTM, and content production; measure portfolio performance with data; lead and develop curriculum directors and managers; define scalable frameworks and represent the company externally.