AI Senior Engineer in Cupertino

• Strong practical experience with GenAI, LLMs and agents AI to software quality engineering and test lifecycle automation .
• Ability to convert requirements, user stories, specifications, API contracts and technical documentation into executable test scenarios and test cases.
• Experience building solutions that analyze requirements for functional gaps, ambiguity, traceability, risk and test coverage.
• Hands-on experience designing multi-agent workflows for requirement analysis, test , defect analysis, validation and quality intelligence.
• Capability to develop AI-assisted mechanisms for defect identification, classification, deduplication, severity assessment, root-cause analysis and automated defect filing.
• Expreience in developing AI/LLM-based validation for multilingual and localized content, including translation accuracy, formatting, connect, truncation, and content consistency.
• Strong understanding accessibility standards such as WCAG2.2 with the ability to build AI-assisted automated checks for accessibility violations across web experiences.
• Strong experience with Automation frameworks API/UI testing , CI/CD integration, test orchestration, reporting.
• Experience building RAG pipelines using embeddings and vector database to ground AI generated test scenarios and validations in approved requirements and product knowledge.
• Ability to define the AI-QE Solution architecture, technical roadmap, reusable accelerators, engineering standard, and measurable business outcomes.
• Strong hands-on expertise in Python and Java/Typescript with experience integrating LLM and AI services through APIs
• Ability to lead technical discussions with QE, engineering, product, and client stakeholders and translate business problems into scalable AI solutions.

Technology Exposure:

• LLMs, RAG, Agentic AI, Prompt Engineering, Multimodal AI, AI Evaluation
• Python, Java/TypeScript
• Playwright, REST API automation, CI/CD
• WCAG 2.1/2.2
• Embedding, Vector DB, Document Parsing