Posted:5 days ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Required Experience:

  • 5–7 years

     in software testing, with

    at least 3 years

     focused on AI/ML applications
  • Proven experience in

    hands-on testing and validation

     of GenAI or ML-based products
  • 2+ years

     of agile testing experience in cross-functional, fast-paced environments
  • Hands-on experience testing

    LLM-based applications

     (e.g., ChatGPT, Claude, Gemini)
  • Strong proficiency in

    prompt engineering

    , model behavior analysis, and edge case identification
  • Experience with

    API testing

     for AI services (OpenAI, Anthropic, Azure AI, Hugging Face)
  • Familiarity with

    AI observability tools

     and testing frameworks (MLflow, Weights & Biases, LangSmith)



Technical Skills:

  • Advanced use of

    test automation tools

     (Selenium, Postman, Pytest, Robot Framework)
  • Deep understanding of

    NLP concepts

     and evaluation metrics (BLEU, ROUGE, perplexity, METEOR)
  • Experience with

    bias detection

    , fairness testing, and adversarial testing in AI systems
  • Knowledge of

    model versioning

    , A/B testing, and performance benchmarking
  • Proficiency in

    Agile testing tools

     (Jira, TestRail, Confluence) and

    CI/CD pipelines

  • Working knowledge of

    transformer architectures

    , fine-tuning, and model interpretability
  • Exposure to

    data drift

    , concept drift, and model degradation monitoring



Key Responsibilities:

  • Design and execute hands-on test cases

     for prompt accuracy, response quality, and safety validation
  • Validate model outputs for

    hallucinations

    ,

    bias

    ,

    toxicity

    , and

    alignment issues

  • Perform

    load and stress testing

     on AI inference endpoints and pipelines
  • Test integration between GenAI models and

    enterprise application workflows

  • Collaborate with product owners to define

    acceptance criteria

     and

    quality gates

  • Participate in sprint ceremonies and contribute to

    release planning

  • Document model behavior patterns, failure modes, and

    test coverage gaps

  • Mentor junior testers and contribute to

    QA best practices

     for AI systems
  • Actively contribute to

    test automation

    ,

    tooling improvements

    , and

    test data generation


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