Staff Quality Assurance Engineer

PearsonHoboken, NJ
$130,000 - $150,000Hybrid

About The Position

We are seeking a Senior Expert, Quality Engineer (QE) with deep expertise in quality engineering for AI-powered systems. In this role, you will own and lead end-to-end quality for your project while playing a key role in testing and evaluating complex, non-deterministic AI systems. You will help shape the quality strategy for the project and raise the overall quality bar for the teams you work with.

Requirements

  • 8+ years of experience in Quality Engineering or Quality Assurance
  • Proven hands-on experience testing AI/LLM-based systems, including agents, multi-agent workflows, and RAG pipelines
  • Experience with AI evaluation approaches (e.g., RAGAS, LLM-as-judge, regression baselines) and non-deterministic testing strategies
  • Strong automation skills using Playwright or a comparable framework
  • Proficiency in JavaScript/TypeScript and/or Java
  • Solid experience with API testing and data validation
  • Demonstrated track record of leading quality end-to-end for complex projects, from strategy through execution
  • Ability to define and drive QE technical direction within a project or product area
  • Experience working in Agile delivery environments and contributing to fast-moving release cycles

Nice To Haves

  • Hands-on experience with prompting, embeddings, or vector databases
  • Cloud experience (AWS preferred)
  • Exposure to AI-assisted development or testing tools (e.g., Cursor, Copilot)
  • Experience with AI observability or monitoring tools for production LLM systems

Responsibilities

  • Define quality strategies and own test planning from requirements through release, partnering closely with cross-functional teams
  • Design and execute scalable functional, regression, and integration testing strategies
  • Apply hands-on automation framework expertise across UI, API, and backend layers to support major product initiatives
  • Test AI-driven functionality, including LLM agents, multi-agent workflows, and RAG pipelines
  • Validate AI outputs for accuracy, relevance, consistency, and edge cases across non-deterministic systems
  • Own evaluation frameworks (e.g., RAGAS), test datasets, and regression baselines for AI features
  • Stay current with the evolving landscape of LLM evaluation, agent testing, and AI observability, and translate emerging techniques into practical testing approaches
  • Lead QE team for your project by setting technical direction, defining quality strategy, and ensuring delivery confidence
  • Contribute to QE standards and frameworks within your project scope, establishing practices that other engineers can adopt
  • Integrate automated tests into CI/CD pipelines and partner with engineering leads to embed quality into the delivery process
  • Leverage data, risk signals, and production insights to continuously improve test coverage and effectiveness

Benefits

  • annual incentive program
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