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XM

Senior AI QA Automation Test Engineer

Posted 17 Days Ago
Be an Early Applicant
Remote or Hybrid
Hiring Remotely in Greece
Senior level
Remote or Hybrid
Hiring Remotely in Greece
Senior level
Lead the adoption of AI technologies in QA processes, develop AI-augmented frameworks, and enhance software testing through AI methodologies.
The summary above was generated by AI
Senior AI QA Automation Test Engineer
 
The Role:
We are seeking a Senior AI QA Automation Test Engineer to serve as our highest-level technical expert and hands-on innovator in the AI and testing space. This is a highly strategic, senior Individual Contributor (IC) role designed for an exceptional technologist. You will partner closely with internal QA leadership to drive the adoption of AI and Generative AI across the entire Software Development Life Cycle (SDLC). 
As our core technical enabler, you will not be responsible for people management; instead, you will act as a force multiplier across the organization. You will architect complex, autonomous systems that fundamentally improve how we analyze requirements, assess risk, predict defects, and validate quality. You will build foundational frameworks, establish technical standards for evaluating AI-based solutions, and empower engineering teams to effectively leverage next-generation agentic QA workflows. 

The main responsibilities of the position include:

  • Acting as the primary technical enabler for the QA organization by building scalable AI/ML frameworks, libraries, and tooling that support broader engineering adoption
  • Collaborating closely with QA, Data Science, and Engineering teams to ensure seamless integration of AI-driven testing capabilities within the CI/CD ecosystem
  • Leading research and experimentation initiatives focused on emerging AI testing methodologies, tools, and best practices
  • Mentoring and supporting engineers through hands-on collaboration, code reviews, technical workshops, and architectural guidance
  • Designing and implementing advanced autonomous QA agents and workflows using modern AI orchestration frameworks and technologies
  • Building sophisticated AI evaluation pipelines to assess reasoning quality, robustness, hallucination rates, fairness, and overall model reliability
  • Developing resilient, AI-augmented, and self-healing automation frameworks capable of adapting to dynamic product and UI changes
  • Implementing machine learning-driven analytics and intelligent quality engineering solutions, including predictive quality insights, root cause analysis, and smart test prioritization 

Main requirements:

  • BSc/MSc in Computer Science, Artificial Intelligence, or related discipline
  • 8+ years of hands-on experience in AQA  
  • 1+ years of experience applying AI or ML technologies in software testing or QA process improvement  
  • A proven history of personally building and integrating AI/ML models into production workflows or SDLC processes
  • Coding proficiency in Java/Python and/or TypeScript, with a deep, practical understanding of complex software architecture and distributed system design
  • Hands-on experience designing and implementing complex AI agent architectures (LLM-as-a-judge, human-in-the-loop, RAG, multi-agent orchestration)
  • Deep architectural knowledge of modern AI/ML tooling (LLMs, vector databases, MLOps pipelines)
  • Strong background in integrating advanced tooling into enterprise CI/CD pipelines (GitLab, Jenkins, GitHub Actions) and containerized cloud-native environments (Docker, Kubernetes)
  • Exceptional ability to communicate complex technical concepts clearly, influence engineering standards without direct authority, and collaborate effectively across disciplines 

The following will be considered an advantage:

  • Extensive experience with autonomous QA agents and agentic orchestration frameworks in building self-evolving test suites
  • Expertise in high-fidelity AI evaluation pipelines and real-time observability (e.g., LangSmith, Arize) to measure probabilistic outcomes and adversarial robustness
  • Knowledge of AI ethics, fairness, and bias detection in model validation
  • Experience with gRPC, WebSockets, and HTTP/2
  • Familiarity with cloud-native AI solutions (AWS Bedrock, GCP Vertex AI, Azure AI) 

Benefit from:

  • Attractive remuneration package
  • Intellectually stimulating work environment
  • Continuous personal development and international training opportunities

The Hiring Experience: What Awaits You

  • Let’s Connect – Intro Chat with Talent Acquisition
  • Deep Dive – First Interview with Your Future Team
  • Final Connection – Final Interview

All applications will be treated with strict confidentiality!

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