Senior QA AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior QA AI Engineer based in India. This role leads quality engineering and AI testing initiatives for reliable, scalable, and secure cloud-based software solutions. You will design advanced testing strategies for backend services, APIs, AI-powered features, and microservices architectures. A key focus will be validating large language model behavior, agentic AI workflows, security risks, and non-deterministic outputs. You will build automated evaluation frameworks that integrate quality controls directly into modern CI/CD pipelines. Working closely with product, engineering, and machine learning teams, you will influence requirements, release quality, and technical standards. The role also provides an opportunity to mentor engineers and drive continuous improvements in quality engineering practices. You will contribute to responsible AI adoption while helping deliver resilient technology for complex risk and decision-making environments.

Lead quality engineering and AI testing initiatives to ensure software solutions are reliable, scalable, secure, and production-ready across cloud-based platforms. Design, develop, and maintain automated test suites for Java-based backend services and REST APIs, supporting consistent quality across development and release cycles. Own testing strategies for AI-powered features, including large language model output validation, regression baselines, tool-call accuracy, context management, and end-to-end integration testing. Develop continuous integration evaluation frameworks for non-deterministic AI outputs using rubric-based scoring, automated prompt regression suites, and behavioral drift detection. Collaborate with product owners, software engineers, and machine learning engineers to establish testable requirements, review acceptance criteria, and maintain quality throughout agile delivery cycles. Perform database validation against PostgreSQL and Microsoft SQL Server to verify data integrity, transformation logic, and backend workflow accuracy. Conduct AI-focused security testing, including prompt injection assessments, adversarial input validation, jailbreak testing, and sensitive data leakage checks. Define and enforce synthetic or masked test-data standards for AI testing, ensuring confidential and regulated information is handled appropriately. Monitor and report quality, performance, and AI observability metrics, including token consumption, streaming latency, tool-call success rates, model error rates, and reliability indicators. Integrate automated testing into CI/CD pipelines and establish effective quality gates and deployment controls. Conduct test-code reviews, mentor quality engineering team members, perform exploratory testing, and continuously improve testing processes and methodologies. Support performance and load testing for cloud-native SaaS platforms hosted on AWS and Microsoft Azure, validating scalability, availability, and reliability. Maintain comprehensive test documentation, traceability matrices, defect analysis reports, and quality metrics to provide transparency and alignment across stakeholders. Requirements: 5–7 years of experience in software quality engineering, with strong hands-on experience testing Java-based backend services and REST APIs. Proficiency with test automation frameworks such as Selenium, TestNG, JUnit, RestAssured, or Cucumber for UI and API testing. Strong knowledge of relational databases, particularly PostgreSQL and Microsoft SQL Server, with experience performing data validation and integrity testing. Hands-on experience testing AI features integrated with large language models, including output validation, semantic evaluation, hallucination detection, regression testing, and streaming API behavior. Familiarity with Model Context Protocol (MCP) and agentic AI testing patterns, including tool-use accuracy, context management, and validation of deterministic versus non-deterministic outputs. Experience conducting AI security testing, including prompt injection, jailbreak validation, adversarial testing, sensitive data leakage assessments, and reliability or performance testing. Strong understanding of software design principles, microservices architectures, and system-level test strategy development. Demonstrated ability to identify complex edge cases and translate technical requirements into comprehensive quality strategies. Strong understanding of AI technologies and experience applying AI tools to support innovation, operational efficiency, and responsible AI adoption. Knowledge of AI risk management, governance, and responsible AI practices. Experience working with cloud-based platforms, preferably AWS and Microsoft Azure. Strong collaboration and communication skills, with the ability to work effectively across product, engineering, machine learning, and quality teams. Experience mentoring engineers and contributing to continuous improvement in testing standards and processes. Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related technical field. Benefits: Full-time remote opportunity based in India. Opportunity to work on advanced AI, software quality, cloud, and automation initiatives. Exposure to large language models, agentic AI, AI security, and responsible AI practices. Opportunity to influence quality engineering strategy and establish modern testing standards. Collaboration with product, software engineering, machine learning, and other technical teams. Opportunity to mentor team members and contribute to the development of high-performing engineering practices. Experience working with cloud-native SaaS platforms across AWS and Microsoft Azure. Opportunity to contribute to technology that supports complex risk assessment, resilience, and informed decision-making. Inclusive environment that values curiosity, diverse perspectives, integrity, innovation, and continuous learning.

laptop-ats-crawler v3