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Open nowPosted yesterday

Principal Software Engineer

Pearson340 open roles

Pay
$150,000 – $170,000 a year
Where
United States
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Your applicationOpen nowPrincipal Software EngineerPearson · United States

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  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Pearson postings stay open a median of 12 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted yesterday

Pearson median: 12 days open

The posting

Job Description

We are modernizing Pearson's content platform into a set of shared platform services. You will be one of the principal engineers leading that work hands-on. You design the target systems and move content and users onto them safely. Full stack here goes beyond front end and back end: the work spans user interfaces, workflow orchestration, AI, backend services, and cloud infrastructure. You will stay deep in design and implementation while raising the technical judgment and execution of the engineers around you.

What you will own

  • The technical plan and delivery for several technology tracks, such as consolidations, migrations, and other large-scale initiatives, from target design through launch.
  • Migrations of large volumes of content and data, such as assessment items or media assets, with verification that nothing is lost or broken for downstream products.
  • Shared capabilities that should be built once and used everywhere, like media handling, search, rendering, or AI content services, exposed through clean APIs.
  • An honest, costed view of the technical debt in your systems and what to fix first.
  • Escalated incidents on your systems: you are the technical point of contact when one has business impact, and you stay on it through root cause and the fix that prevents a repeat.
  • Security and stability for the applications you own. That covers runtime and framework upgrades, vulnerability and penetration test remediation, secure data handling, and disaster recovery plans that are documented, exercised, and audit ready.
  • Shared standards across teams for design patterns, tooling, reliability, observability, performance, and evaluation, including how AI-powered workflows are measured, tested, and kept safe.
  • The long-term technical roadmap for your area, and the subject-matter expertise that comes with it.

How you will work

This is a hands-on engineering role, not an architecture role. You will not be embedded in a single team; you will work across the platform on initiatives and technical problems that matter most to leadership. You own the designs, the code on the critical path, and the engineering calls that decide whether an initiative succeeds. You should enjoy defining the problem as much as solving it.

  • Write production code where the risk is highest and review the hardest changes from other engineers.
  • Unblock hard technical problems that span systems, teams, or domains.
  • Work with engineering managers, product managers, architects, and quality engineering. When long-term initiatives and current delivery compete for the same people or code, make the tradeoff visible and help decide it.
  • Work directly with the people who use the platform across Pearson's lines of business, and separate the foundational problems from the incremental ones before the team commits.
  • Spot opportunities that cut across team and product boundaries, bring stakeholders to a shared direction, and carry the work from exploration through launch and iteration.
  • Make high-consequence technical decisions under ambiguity, balancing speed and learning against scalability, simplicity, and long-term maintainability. Hold views grounded in evidence, and change them when the evidence changes.
  • Evaluate frameworks, tools, and vendors, and pilot practices like contract testing, automated regression, and zero-downtime migration before teams adopt them.
  • Run technical feasibility reviews for new AI capabilities, and work with internal teams and external partners to assess and co-develop them.
  • Use AI coding tools daily, particularly for large upgrades and refactors, and help teams adopt them with sound review habits.
  • Act as a technical multiplier: review critical designs, mentor engineers, and improve engineering practices. Success includes the senior engineers around you becoming owners of these systems too.

Minimum qualifications

  • 12+ years building and operating production software, including 4+ years at staff or principal level, or as technical lead across several teams or a large multi-service system.
  • Led a re-platforming or legacy migration of a production system with active users and data, through to switching off the old system.
  • Led the design and delivery of technically complex, user-facing systems.
  • Upgraded or migrated production systems off an end-of-life runtime or framework.
  • Full-stack depth in our core stack: Java and Spring Boot, Node.js and TypeScript, and React, with MongoDB and event-driven services (SQS, SNS, Kafka) behind APIs with many consumers.
  • Production experience on AWS, especially ECS Fargate, Lambda, S3, and API Gateway, with observability (New Relic, CloudWatch), CI/CD (GitHub Actions), and infrastructure as code (Terraform).
  • Writes clear design documents and migration plans, explains tradeoffs to engineering, product, and executive audiences, and influences without authority, especially when the decision carries real uncertainty. We will ask you to walk us through a document you wrote.
  • Bachelor's degree in Computer Science or an equivalent combination of education and experience.

Preferred qualifications

  • Content platform experience: authoring and content management, digital asset management, content transformation pipelines, content delivery, or assessment systems.
  • Content and learning standards such as EPUB, XML/XSLT, QTI, or LTI.
  • Built or operated an LLM-backed feature in production, using Python and services such as AWS Bedrock or Azure OpenAI, and understands the problems AI brings: nondeterminism, evaluation, latency, and safety.
  • Moved a product off a commercial platform, such as a DAM or CMS, onto in-house services.
  • Search and caching with OpenSearch or Solr and Redis.
  • Worked with distributed teams and delivery partners across US and India time zones.

About PSG-CP

Pearson is the world's lifelong learning company. PSG-CP (Pearson Software Group - Content Platform) builds and runs the platform behind how Pearson creates, delivers, and measures learning content, for every Pearson line of business.

Apply now and help shape the future of learning.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows:

The full-time salary range is between $150,000 - 170,000.

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

Applications will be accepted through 12th of December. This window may be extended depending on business needs.

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