Key ResponsibilitiesLead the design and implementation of API automation frameworks using Karate for microservices-based architecturesBuild and support backend services using Java and Spring Boot to enable scalable and testable systemsDevelop and maintain automated test suites for REST APIs and distributed systemsIntegrate automated testing into CI/CD pipelines to support continuous deliveryOwn the assessment of current QA/testing capabilities, including tools, processes, and automation maturityDefine and implement a target-state testing strategy leveraging AI-driven quality engineering practicesIdentify, design, and deploy AI-powered solutions across test generation, test data management, regression optimization, and defect detectionDevelop and execute a phased roadmap for AI adoption in testing, from pilot to enterprise rolloutLead implementation and scaling of AI-enabled testing solutions across teams and environmentsUse AI to analyze logs, failures, and test results to accelerate root cause analysis and improve system reliabilityDrive continuous improvement in test coverage, execution efficiency, and defect leakage reductionCollaborate with engineering, product, and DevOps teams in an Agile environmentMentor team members and establish best practices in automation and AI-driven testingRequired Qualifications7+ years of experience in QA automation, testing, or SDET roles, with leadership responsibilitiesStrong programming experience in Java and frameworks such as Spring BootHands-on expertise with Karate for API automation testingDeep understanding of REST APIs, microservices, and distributed systemsExperience with AWS services (e.g., Lambda, ECS, S3, CloudWatch)Proven experience integrating testing into CI/CD pipelinesDemonstrated experience applying AI/ML or GenAI in testing or software engineering workflowsExperience using AI tools to generate test cases, optimize test suites, or automate failure analysisAbility to define AI-driven testing strategies and lead implementation/rollout across teams. The ideal candidate will not only lead automation efforts but will define, implement, and scale AI-driven testing capabilities, improving efficiency, coverage, and release confidence across complex systems.