Lead the design and development of AI-assisted quality engineering solutions using LLMs, generative AI, and multi-agent workflows. Responsibilities include automated test generation, requirements analysis, defect detection and management, multilingual validation, accessibility testing, API and UI automation, CI/CD integration, RAG and vector database implementation, and AI solution architecture. The role also defines technical roadmaps, reusable accelerators, engineering standards, and business outcomes while collaborating with quality engineering, product, engineering, and client stakeholders.
*Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.*
Location: Sunnyvale, CA (hybrid)
Requirements:
- Strong understanding of applying GenAI, LLMs and agents AI to software quality engineering and test lifecycle automation .
- Ability to design and generate test scenarios, test cases, and test data from requirements, user storied, specifications, API contracts and technical documentation.
- 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 generation, 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 with embeddings, vector databases, RAG, knowledge bases, structured/unstructured data processing, and enterprise content integration.
- 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
Kaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, spouse of protected veteran, or disability.
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