Leads the design and development of AI-powered quality engineering solutions for requirements analysis, test generation, defect detection, validation, accessibility, localization, and test lifecycle automation. Builds multi-agent workflows, RAG pipelines, LLM integrations, automation frameworks, and CI/CD orchestration using Python and Java or TypeScript. Defines solution architecture, technical roadmaps, reusable accelerators, engineering standards, and measurable outcomes while collaborating with engineering, QE, product, 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 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 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 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
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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