Principal Software Engineer
Budget / Salary$155,000–175,000
TypeFull-time job
LocationUnited States
Posted3 hours ago
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.
Originally posted on Himalayas
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.
Originally posted on Himalayas
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