DevRev is hiring a Lead AI Test Automation Engineer

About the Role

Role details below.

Responsibilities

• Design and implement comprehensive testing strategies for GenAI features, including conversational AI, agentic systems, and LLM-powered workflows
• Develop automated test suites for prompt testing, including regression tests that detect unintended changes in model behaviour
• Create evaluation frameworks to measure GenAI quality across multiple dimensions (accuracy, relevance, safety, consistency, latency)
• Build and maintain test datasets and golden examples that represent diverse user scenarios and edge cases
• Implement monitoring and alerting systems to detect quality degradation in production GenAI features
• Perform adversarial testing to identify potential failures, hallucinations, biases, or security vulnerabilities in AI systems
• Collaborate with engineers to define acceptance criteria and quality gates for AI feature releases
• Develop tools and frameworks that make it easy for engineers to test their GenAI implementations
• Conduct user acceptance testing and gather feedback on AI feature performance from internal users
• Document testing procedures, known issues, and quality metrics in clear, accessible formats
• Partner with Product and Design teams to ensure AI features meet user experience standards
• Stay current with GenAI testing methodologies, tools, and industry best practices

Requirements

• PRE or test engineering experience, preferably with AI/ML systems
• Strong understanding of GenAI technologies including LLMs, prompt engineering, and AI application patterns
• Experience with test automation frameworks and scripting (Python, JavaScript, Selenium, Pytest)
• Knowledge of software testing methodologies (functional, integration, regression, performance, security testing)
• Ability to design test cases and evaluation criteria for non-deterministic systems
• Strong analytical and problem-solving skills with attention to detail
• Experience with API testing tools (Postman, REST Assured) and backend testing
• Familiarity with CI/CD pipelines and automated testing integration
• Excellent communication skills for documenting issues and collaboration

Nice to Have

• Experience testing conversational AI, chatbots, or agentic systems
• Knowledge of ML model evaluation metrics and techniques
• Familiarity with LLM evaluation frameworks (LangSmith, PromptFoo, Ragas)
• Experience with performance testing and load testing AI APIs
• Understanding of responsible AI principles, including fairness, transparency, and safety testing
• Background in enterprise software or SaaS QA
• Experience with test management tools (TestRail, Zephyr, Jira)
• Knowledge of security testing methodologies for AI systems
• Scripting experience with Python, including working with LLM APIs

Benefits

• Define Quality practices for GenAI applications
• Work on cutting-edge AI technologies and help ensure they're reliable and trustworthy
• Shape quality standards that will impact