Senior Software Engineer in Test (SET) - GenAI Focus

We are looking for a Senior Software Engineer in Test with a strong technical background in test automation and specialized expertise in Generative AI (GenAI) and AI-driven testing. In this role, you will lead the integration of AI-powered capabilities into our testing frameworks, CI/CD pipelines, and quality workflows to maximize automation coverage, efficiency, and product intelligence.

Responsibilities

• AI-Driven Test Automation Strategy: Lead the design and implementation of next-generation test automation frameworks enhanced by Generative AI and agentic workflows
• GenAI Tooling & Utilities: Develop, maintain, and scale custom AI-assisted utilities, agents, and APIs for automated test generation, test data synthesis, self-healing tests, and intelligent root cause analysis
• CI/CD & AI Observability Integration: Integrate GenAI capabilities into CI/CD pipelines for automated regression analysis, test monitoring, and quality gating. Use AI observability tools to monitor the behavior and reliability of AI-assisted test components
• Test Automation & Quality: Build, maintain, and execute robust automated test suites across multiple programming languages and platforms, ensuring high code quality and testability
• Tool Evaluation & Innovation: Conduct evaluations of emerging AI-driven testing tools and GenAI models, recommending and prototyping the best fit for project needs
• Collaboration & Leadership: Collaborate closely with developers, DevOps engineers, and product teams to enforce best coding practices, conduct code reviews, and drive AI adoption across the SDLC
• Client Engagement: Demonstrate AI-based automation prototypes to clients, explaining their value propositions, assumptions, limitations, and architectural patterns

Requirements

• Experience: 3+ years of Software Engineering experience in Software Testing, Test Automation, DevOps Automation, and Software Development
• Core Test Automation & Programming: Advanced proficiency in test automation, with hands-on expertise in at least one core programming language (e.g., Python, Java, JavaScript, or .NET)
• GenAI & AI-Driven Testing (Must-Have):
• Solid practical knowledge of Generative AI, LLMs, prompting techniques, and AI APIs applied directly to QA and automation workflows
• Hands-on experience using GenAI tools to accelerate test design, automation code development, debugging, and synthetic test data generation
• Understanding of agentic workflows, AI evaluation principles, and AI model/system observability
• DevOps & CI/CD: Advanced hands-on experience integrating test automation suites with DevOps and CI/CD pipelines
• Software Engineering Practices: Strong grasp of software design patterns, clean coding standards, static code analysis, and branching strategies (e.g., Git Flow)