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Pearson VUE
Pearson VUE
1001 – 5000 Darbinieki
KonsultācijasLoģistikaVeselības aprūpe
Pearson VUE nodrošina datorizētas testēšanas un kvalifikācijas piešķiršanas pakalpojumus dažādu nozaru, tostarp konsultāciju, veselības aprūpes un loģistikas, organizācijām. Tās platforma atbalsta augstas nozīmes sertifikācijas un profesionālos eksāmenus, kā arī piedāvā rīkus eksāmenu plānošanai, kandidātu resursiem un testēšanas pielāgojumiem. Palīdzot eksāmenu īpašniekiem novērtēt prasmes un kandidātiem apliecināt savas zināšanas, Pearson VUE veicina profesionālo attīstību un nozares standartus. Uzņēmuma personāla atlases konteksts ietver lielu starptautisku komandu, kas koncentrējas uz vērtēšanas nodrošināšanu un kandidātu pieredzi.
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Vakances uzņēmumā

Software Engineering Manager, AI and Data Platforms

Lead AI fluent engineering and modernize Pearson VUE’s Data Foundations platform. Maintain service continuity while advancing cloud, data, and agentic capabilities for Pearson Virtual Schools.

USAmerikas Savienotās ValstisNCZiemeļkarolīnaAttālinātiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuFull-stack inženierisProgrammatūras inženieris
.NETAngularASP.NETAWSjQueryMākonisReactSQLTypeScript

Apraksts

  • Set team priorities, delivery commitments, and operating practices.
  • Assign work, handle escalations, clear blockers, and improve processes.
  • Hire engineers and uphold expectations for AI fluent engineering.
  • Apply guardrails, human review and fallback, escalation paths, and disclosure for agentic features across relevant product surfaces.
  • Require evaluation sets with defined pass criteria and release gates before model backed features reach students.
  • Track reliability, hallucinations, model performance, and drift against established thresholds.
  • Require specification first development, contract and negative testing, automated merge gates, and model based evaluations.
  • Guide contributions to governed shared libraries, MCP servers, evaluation suites, and golden datasets.
  • Develop team skills, lead performance and career discussions, and build succession plans.
  • Deliver Data Foundations engineering work, including roadmaps, platform readiness, migration sequencing, cutover planning, dependency management, and coordination between source systems and downstream users.
  • Set standards for data contracts, quality gates, lineage, observability, access controls, operational readiness, and support ownership.
  • Work with Product, Data Engineering, Data Analytics, Solution Architecture, Security, Compliance, DevOps/SRE, and vendor teams.
  • Move legacy .NET, ASP.NET WebForms/MVC, AngularJS, jQuery, and SQL Server platforms toward React, TypeScript, modern .NET REST services, containers, AWS, and event driven APIs while maintaining platform continuity.

Prasības

  • At least four years managing engineers who deliver production software, including hiring, performance management, and development.
  • An engineering background that supports reviewing technical decisions and earning credibility with AI fluent engineers.
  • Experience delivering model backed or agentic features to real users, including pre release evaluation and post release monitoring.
  • Experience maintaining quality gates while meeting delivery demands.
  • Experience managing legacy and target platforms at the same time.
  • Ability to lead a distributed team across time zones with strong written communication practices.
  • Experience in regulated or privacy sensitive environments; K-12 and FERPA experience is an advantage.
  • A relevant degree or equivalent practical experience.
  • Knowledge of artificial intelligence, information security, problem solving, technical judgment, API management, cloud computing, data security, DevOps, software design, AI agents, AutoAI, LLMs, generative AI, evaluation of AI generated content quality, performance management, code review, delivery of AI enabled capabilities, measurement of AI tooling adoption, reusable engineering tools, evaluation suites, data foundations, integration and migration oversight, reliability, observability, and testing.

Priekšrocības

  • Remote work arrangement.
  • Full time employment.

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