Senior QA AI Engineer

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.

• 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.