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Job Summary:

Ciena is seeking a highly motivated and skilled AI Verification Engineer to join our growing team. You will be responsible for the verification and validation of AI/ML models and their integration within our networking products and solutions. You will play a critical role in ensuring the quality, performance, and reliability of our AI-powered offerings, contributing to the next generation of intelligent networks.

Verification and Validation:

· AI Agent & Application Testing Strategy: Design, develop, and execute comprehensive test plans, strategies, and test cases specifically tailored for LLM-powered AI agents and applications.

· Adversarial, Robustness & Edge Case Testing: Proactively design and implement adversarial attack simulations, stress tests, and sophisticated techniques to identify and test edge cases, ensuring the robustness, safety, and resilience of AI agents against unexpected, novel, or malicious inputs. Knowledge of attack prevention strategies to counteract RAG poisoning, Prompt injection

· Comprehensive Test Methodologies for AI: Strong knowledge and practical application of a wide range of testing types (functional, non-functional, performance, integration, security, usability, A/B testing, metamorphic testing, etc.) and proven ability to adapt and innovate them for the unique challenges of AI systems

· RAG & Knowledge Base Validation: Rigorously test and validate the effectiveness, accuracy, concurrency, and relevance of RAG pipelines and knowledge base integrations in enhancing AI agent performance, knowledge grounding, and preventing information leakage. Collaborate with development teams to optimize AI/ML model performance and efficiency within resource constraints. Investigate and resolve performance issues in AI/ML-driven network applications.

· Prompt Engineering: Develop, test, and optimize effective prompts for LLMs. Continuously analyze model responses and iteratively redefine prompts to improve accuracy and context relevance. Document prompt strategies and outcomes to build reusable prompt libraries and knowledge bases. Evaluate model performance on different prompts using qualitative and quantitative metrics. Explore and implement prompt engineering techniques such as zero-shot, few-shot, and chain-of-thought prompting. Troubleshoot and mitigate undesired outputs including bias, hallucination, or

security risks arising from prompts. Contribute to AI/ML model fine-tuning project requirements with prompt engineering expertise.

Research and Development: Stay up to date with the latest advancements in AI/ML verification and validation techniques. Research and evaluate new tools, technologies, and methodologies for AI/ML testing. Contribute to the development of best practices and standards for AI/ML verification at Ciena.

Qualifications: Bachelor’s or master’s degree in computer science, Data Science, Machine Learning, or related fields.

Experience: Background in QA with specific experience in testing cloud-based AI/ML solutions

Skills:

· Strong understanding of AI/ML concepts and techniques

· Familiarity with common AI/ML model development frameworks

· Programming skills in Python or other relevant programming languages.

· Understanding of APIs and API programming

· Database experience – SQL or any other database system

· Experience with data analysis and visualization tools. Experience working with large datasets and data pipelines.

· Experience with DevOps practices and CI/CD pipelines.

· Knowledge of security vulnerabilities and their impact on AI/ML models is a plus

· Nice to have: Google ADK experience

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Ciena is an Equal Opportunity Employer, including disability and protected veteran status.

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