Principal Software Engineer

Role Overview

Pearson Virtual Schools is transforming how learners experience education online. As our technology and programs evolve, so does how we design, build, and deliver them.

Individuals in the Software Engineer roles design, develop, test, and maintain software applications aligned with the company’s technical and functional architecture. They translate complex business requirements into scalable technical solutions, grounded in a deep understanding of the business, its drivers, and industry trends. They are responsible for software quality through thorough testing and lifecycle management. They collaborate with cross-functional teams to align on strategic objectives and deliver value through continuous improvement.

Principal Software Engineers are relied upon to independently lead the delivery of technically challenging solutions within major product lines or back-end systems that support business revenue, regulatory needs, or operational continuity. At this tier, individuals solve intricate problems, advise on architecture choices for high-profile features, and frequently act as technical point of contact during escalated incidents with measurable business impact. They coordinate evaluation of new frameworks and tools, pilot advanced coding practices, and review the work of less experienced engineers for critical projects. The engineer’s influence regularly extends to cross-team collaborations, with their contributions making the difference in project timelines, technical debt, and system performance. Risk exposure involves safeguarding the stability and security of mid- to large-size applications and averting delivery or operational failures.

This role sits where three Pearson Virtual Schools programs meet: Content Foundations, Data Foundations and Adaptive Learning. You will own the technical architecture that connects AI-ready learning content and trusted learner data to adaptive, AI-powered learning experiences for K-12 students.

• Key Responsibilities
• Cross-Program Technical Leadership
• Own the end-to-end technical design where three programs meet: structured learning content, learner and performance data, and adaptive learning experiences
• Define the shared contracts between content, data and adaptive services so each program can move independently without breaking the others
• Advise on architecture choices for high-profile adaptive features, and make the tradeoffs between speed, quality and long-term platform health explicit
• Act as the technical point of contact for escalations that span more than one program, and drive them to resolution

AI-Powered Adaptive Learning

• Design and build LLM- and agent-driven capabilities that personalize the learning path based on what a student knows, where they struggle and how they learn
• Establish evaluation suites and quality gates for AI-generated content and recommendations, covering accuracy, pedagogy, safety and bias
• Lead the evaluation of new models, frameworks and tools, and pilot advanced practices such as retrieval, tool-using agents and MCP servers before scaling them
• Partner with curriculum and learning design experts so that adaptive behavior reflects sound learning science, not just technical possibility

Execution & Delivery

• Build working prototypes quickly to test ideas with real learners and educators, then harden the ones that prove out into production-grade services
• Reduce systemic risk through refactoring, hardening and observability across the content, data and adaptive services you touch
• Safeguard the security and privacy of student data in every design, meeting the standards expected of a K-12 education provider
• Mentorship & Influence
• Model AI-first engineering, using agents throughout design, build, test and review, and help teams across the three programs do the same
• Review critical designs and code from engineers across teams, and raise the bar through example rather than mandate
• Facilitate knowledge transfer between teams so that patterns proven in one program are reused in the others

Domain Depth for This Posting

Adaptive learning:

• Model each student’s current state: mastery, gaps and engagement
• Suggest the next best activity for every learner
• Generate interactives across modalities: text, visual, audio, practice and simulation
• Adapt the full course path: remediate, re-sequence or accelerate
• Give teachers insight into strengths, weaknesses and where to intervene

Content foundations:

• Structured, AI-ready curriculum content that can be authored, tagged, assembled and generated
• A learning object repository to find, reuse and fill gaps in existing resources
• Data foundations: a large-scale student, curriculum and assessment data platform that supplies trusted learner signals to adaptive experiences
• Systems you will shape:
• Learner model service
• Recommendation and course adaptation engine
• Multimodal interactive generation services
• Teacher insights and intervention tools
• Learning object repository, content authoring and publishing services
• Learner data pipelines, APIs and the AI services that connect them
• Partner functions you cannot deliver without: Product Management, Learning Science, Design & Curriculum, Data Science & Data Engineering, Solution & Enterprise Architecture, Platform and Security Engineering

Preferred Qualifications

• 8-12 years of software engineering experience, including technical leadership of complex, cross-team initiatives
• Hands-on experience building production applications with large language models and AI agents, including prompt and retrieval design, tool use and evaluation
• Experience designing data models and pipelines that turn learner or user behavior into signals a product can act on
• Experience with structured content models, content authoring tools or content delivery platforms
• Strong cloud-native engineering background (AWS preferred), with API-first and event-driven design
• Background in education, teaching, learning design or ed-tech is a strong plus
• Track record of turning a rough proof of concept into a durable platform that others build on
• Relevant degree in Computer Science or equivalent practical experience

Skills and Experience

The skills and experience this role are assessed against.

• Adaptability
• Artificial Intelligence
• Learning to Learn
• Engineering fundamentals
• Collaboration
• Information Security
• Innovation
• Problem Solving
• Technical Acumen
• Role-specific skills
• API Management
• Cloud Computing
• Data Security
• DevOps
• Ethical Responsibility
• Resilience Planning
• Software Design
• Emerging skills
• AI Agents
• Automated Artificial Intelligence (AutoAI)
• Specialist depth for this role
• Adaptive learning design, including learner mastery modeling and personalized sequencing
• Evaluating AI-generated learning content and recommendations for accuracy, pedagogy and safety
• Modeling structured curriculum content so it can be reused, assembled and generated

Compensation at Pearson is influenced by factors including skill set, experience, and location.

The full-time salary range for this role is $155,000 – $175,000. This position is eligible to participate in an annual incentive program. Information on benefits can be found here.

Applications will be accepted through 16th November 2026. This window may be extended depending on business needs.

Apply today and imagine the impact you can make.
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