Jobs at Pearson

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Lead cross-functional delivery of School IT Services programs for K-12 virtual and blended operations. Translate roadmap into project plans, manage risks and dependencies, coordinate engineering/IT/security/vendor teams, drive 4-in-the-box operating cadence, communicate to stakeholders, and support release readiness, training, and adoption aligned to the school year.

Improve performance and scalability of web applications by identifying and resolving front-end and back-end bottlenecks. Optimize load times, API responses, and database queries; develop scalable features across the stack, monitor performance, conduct code reviews, troubleshoot production issues, and collaborate with product, design, and engineering teams.

Lead research, design, and deliver Pearson's scalable learner model and AI-driven features. Partner with product, engineering, and design to define data requirements, build prototypes, maintain data pipelines, ensure data quality, and translate research into production ML capabilities and business growth.

Lead a small product analytics team to drive data-informed product decisions for Higher Education courseware. Define KPIs across commercial and learning outcomes, own instrumentation and telemetry, scale experimentation (A/B tests), surface discovery insights, govern data quality, and communicate findings to executives. Partner with product, design, and engineering to embed analytics as a product capability.

Serve as a customer-facing implementation lead for complex Access sales opportunities, coordinating cross-functional teams, tracking milestones/risks, ensuring delivery quality, reporting KPIs/SLAs, and driving continuous improvement and compliance for delivery models.

Perform quality assurance on published content and forms across paper and online formats. Verify text and artwork accuracy, confirm edits, track work queues, document issues, assist Program Lead, complete training, and support continuous improvement. May work overtime to meet deadlines.

Lead end-to-end quality engineering for AI/LLM systems: define quality strategy, design/execute automated tests (UI, API, backend), evaluate non-deterministic AI outputs, build evaluation frameworks and baselines, integrate tests into CI/CD, and lead QE delivery for complex projects.

Designs and operationalizes sales incentive programs, partners with Sales, Finance, HR, and Ops, administers and validates commission calculations, supports SPM tool implementation, drives governance, launch readiness, and continuous improvement of compensation processes.

Drive revenue growth for Pearson's Test Prep portfolio in India by owning territory accounts, prospecting, and managing the full sales cycle. Use consultative solution selling to position digital and blended products, run discovery and demos, develop proposals, close deals, and manage renewals and expansions. Collaborate with marketing, product, customer success, finance, and operations to ensure adoption, forecast accurately in CRM, and provide market feedback to improve offerings.

Manage contract lifecycle for high-profile authors, ensuring contract and royalty data accuracy, reducing suspense accounts, enforcing SLAs and controls, maintaining data governance, resolving queries, mentoring associates, and liaising with stakeholders to mitigate operational risk.

Manage and guide authors to produce pedagogically sound, build-ready course content. Participate in planning, onboarding, editing (developmental and line), apply accessibility and quality standards, coordinate reviews and stakeholders, use authoring tools and AI to improve efficiency, and track schedules, scope, and risks to meet product plan goals.

Implement, test, and deliver assigned features within sprints; write clean, well-documented code; participate in code reviews; collaborate with seniors, QA, and product; learn new tools and contribute to improving codebase and processes.

Deliver end-to-end features for microservices-based systems, focusing on reliability, performance, testing, and production troubleshooting. Collaborate with product, QA, and DevOps, mentor junior engineers, adopt AI-assisted development, and improve system stability and delivery practices.

Lead strategy and design for early learning assessment and instructional systems across literacy and numeracy. Provide product and content guidance, ensure developmental appropriateness, support alignment with state screening/progress monitoring, guide instructional ecosystems and AI-assisted supports, contribute research and thought leadership, and collaborate cross-functionally to translate evidence into practical early learning solutions.

Lead architecture and delivery of scalable, secure web applications; drive AI-first engineering and LLM integrations; write full-stack production code; mentor engineers; promote best practices in microservices, cloud-native, CI/CD, observability, and security.

Lead communications for a large transformation programme: develop and execute communication and engagement plans, create content and leadership messaging, manage stakeholder engagement, support change adoption, run events, ensure consistent messaging across workstreams, and monitor impact using feedback.

Coordinate and drive incident response in a 24x7 environment: initiate bridges, communicate with stakeholders, track and remediate incidents to resolution, document post-incident reviews, and recommend process improvements to improve service reliability and customer experience.

Manage secure, accurate production of assessment content and question papers; coordinate external assessment associates; meet strict deadlines; escalate process issues; support colleagues and examiners; adapt to new systems and qualifications.

Lead learning science for student-facing assessment and AI-assisted learning experiences. Translate research into product requirements, guide intelligent practice and review systems, shape learning library strategy, design experiments and evaluations, and collaborate cross-functionally to ensure instructionally meaningful, standards-aligned, and student-centered learning supports.