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Pearson VUE

Software Engineering Manager

Pearson VUE

. Manage engineers building and operating Pearson Virtual Schools’ Connexus student, curriculum, and assessment data platform and related products .

Posted 10/14/2026full-timeColombo • Sri LankaJuniorMid-LevelWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing engineering teams to deliver AI-fluent products while ensuring compliance with FERPA and data security standards. Proficient in overseeing model-backed capabilities, legacy system migration, and maintaining high-quality delivery under pressure.

Highest-signal resume keywords
Team ManagementAI-Fluent EngineeringModel-Backed Capability DeliveryLegacy System MigrationFERPA Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Engineering ManagementModel EvaluationSQL ServerPostgreSQLAPI ManagementCloud ComputingDevOpsSoftware DesignPerformance ManagementCode Review
Soft Skills
CoachingProblem SolvingWritten CommunicationTeam CollaborationResilience Planning
Tools & Technologies
Connexus Data PlatformMCP ServersEvaluation SuitesGolden DatasetsAutomated Merge Gates
Industry Keywords
FERPAK-12 EducationPrivacy-Sensitive EnvironmentsAI AgentsGenerative AI

Tech Stack

Tools & technologies
CloudPostgresSQL.NET

About the role

Key responsibilities & impact
  • Manage engineers building and operating Pearson Virtual Schools’ Connexus student, curriculum, and assessment data platform and related products
  • Allocate daily work, provide immediate support, and maintain reliable delivery schedules
  • Give timely feedback and escalate unresolved issues early
  • Own onboarding and ramp-up for new team members
  • Hire engineers against the organization’s AI-fluent engineering standards
  • Apply guardrails, human-in-the-loop fallback, escalation, disclosure, and evaluation requirements to agentic product capabilities
  • Require evaluation sets with stated pass bars and release gates before model-backed behavior reaches students
  • Monitor reliability, hallucination, model performance, and drift against stated thresholds
  • Enforce specification-first practices, contract-level tests, negative tests, automated merge gates, and model evaluations
  • Drive contributions to shared libraries, MCP servers, evaluation suites, skills, and golden datasets
  • Coach engineers on the job and recognize contributions specifically
  • Build team understanding of Connexus data foundations across student, enrollment, curriculum, assessment, progress, attendance, and school operations data
  • Lead migration and cutover execution, including legacy analysis, reconciliation, rollback planning, dependency coordination, and production-readiness validation
  • Guide translation of legacy SQL Server, stored procedure, and .NET behavior into PostgreSQL schemas, APIs, events, and domain contracts
  • Apply FERPA-sensitive data boundaries, externalized authorization, and audit-ready controls

Requirements

What you’ll need
  • 2+ years managing engineers who ship to production, including hiring, performance, and development
  • Working engineering background sufficient to review technical decisions and be credible with AI-fluent engineers
  • Experience delivering a model-backed or agentic capability to real users, including evaluation before release and monitoring afterward
  • Experience holding a quality gate under delivery pressure
  • Experience managing legacy and target platforms simultaneously while continuing to ship
  • Comfortable managing a distributed team across time zones with strong written discipline
  • Experience in regulated or privacy-sensitive environments; K-12 and FERPA exposure is an advantage
  • Relevant degree or equivalent practical experience
  • Knowledge of artificial intelligence, information security, problem solving, technical acumen, API management, cloud computing, data security, DevOps, ethical responsibility, resilience planning, and software design
  • Knowledge of AI agents, AutoAI, large language models, generative AI, evaluation of AI-generated content quality, performance management, and code review

Benefits

Comp & perks
  • Hybrid work arrangement
  • Full-time employment