QA Engineer Job in Gurgaon at ciena

Ciena is hiring for the role of QA Engineer!

Responsibilities of the Candidate:

• 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.

Requirements:

• 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