Software Quality Engineer (uk)

Writer Writer · AI Frontier · London, United Kingdom · Engineering, product & design

Software Quality Engineer for an enterprise generative AI platform, focusing on AI agents and LLM-powered applications. Responsibilities include defining QA strategies, developing automation frameworks, collaborating with ML engineers and data scientists, driving process improvements, defect tracking, and monitoring production systems. Requires experience in testing complex distributed systems or AI/ML applications, proficiency in Python/Typescript, and understanding of AI/ML concepts.

What you'd actually do

  1. Define and implement comprehensive quality assurance strategies and test plans for our AI agents and LLM-powered applications, ensuring exceptional product reliability and performance.
  2. Designing and developing automation frameworks: creating robust, scalable, and maintainable automated test frameworks from scratch or enhancing existing ones. You’ll need proficiency in at least one language like Typsecript, Python.
  3. Collaborate closely with product managers, machine learning engineers, and data scientists to understand complex AI features and model behaviors, translating them into effective test cases and validation criteria.
  4. Drive the continuous improvement of our testing processes and infrastructure, integrating automated checks within our CI/CD pipelines to ensure rapid, high-quality releases.
  5. Identify, document, and track software defects and inconsistencies, performing root cause analysis to provide actionable feedback to development teams.

Skills

Required

  • 5+ years of hands-on experience in software quality assurance or engineering
  • strong focus on testing complex distributed systems or AI/ML applications
  • Proficiency in programming languages like Python or Typescript for test automation
  • experience with modern testing frameworks such as Playwright
  • Solid understanding of AI/ML concepts, including model evaluation metrics, data pipelines, and the unique challenges of testing generative AI outputs
  • Exceptional analytical skills
  • keen eye for detail
  • Collaborative spirit
  • Demonstrated ability to drive initiatives independently
  • thrive in a fast-paced, evolving startup environment

Nice to have

  • Experience with cloud platforms (AWS, Azure, GCP)
  • containerization technologies (Docker, Kubernetes) in a CI/CD environment

What the JD emphasized

  • rigorous quality strategies
  • unique challenges of AI quality assurance
  • AI agents
  • LLM-powered applications
  • enterprise-grade LLMs
  • AI agents
  • complex AI features
  • AI model performance
  • AI solutions
  • agentic AI systems
  • AI skills
  • testing complex distributed systems or AI/ML applications
  • testing generative AI outputs

Other signals

  • AI agents
  • LLMs
  • quality assurance
  • test automation
  • CI/CD