QA Engineer- AI Application

As the global leader in high-speed connectivity, Ciena is committed to a people-first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual growth, well-being, and belonging. We re a technology company that leads with our humanity driving our business priorities alongside meaningful social, community, and societal impact. How You Will Contribute: As an AI Verification Engineer , you will report to the [Insert Hiring Manager Title or Name], and work closely with cross-functional teams to ensure the quality, performance, and security of AI-powered components embedded within Ciena s intelligent networking solutions. You will be a key player in validating AI/ML models, prompt engineering strategies, and knowledge base integrations to drive scalable and trustworthy AI solutions. Key responsibilities include: Designing and executing comprehensive test strategies and frameworks for LLM-powered AI agents and applications. Conducting adversarial and edge-case testing to ensure robustness and mitigate risks such as RAG poisoning or prompt injection. Validating the accuracy, concurrency, and effectiveness of RAG pipelines and knowledge base integrations. Engineering and optimizing prompts for generative models using techniques like zero-shot, few-shot, and chain-of-thought prompting. Collaborating with AI/ML and DevOps teams to resolve performance issues and contribute to continuous improvement efforts. The Must Haves: Bachelor s or Master s degree in Computer Science , Data Science , Artificial Intelligence , or a related field. 4+ years of experience in software testing, preferably focused on AI/ML or cloud-based systems. Proficient in Python or similar programming languages. Hands-on experience with AI/ML model testing methodologies (functional, performance, integration, security, metamorphic testing, etc.). Working knowledge of APIs , SQL/NoSQL databases , and CI/CD pipelines . Experience validating and troubleshooting large-scale datasets, data pipelines, and LLM applications. Understanding of AI vulnerabilities and risk mitigation strategies in model validation. Assets: Experience with prompt engineering , including iterative refinement and prompt performance evaluation. Familiarity with frameworks such as TensorFlow , PyTorch , or Google ADK . Exposure to testing and evaluating RAG pipelines and knowledge-grounded AI systems. Background in AI system security , including adversarial testing and prevention strategies. Strong communication skills and the ability to document reusable test and prompt strategies effectively. #LI-FA Not ready to apply? Join our Talent Community to get relevant job alerts straight to your inbox. At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.