AI Lead Engineer
About The Position
This role focuses on applying Generative AI (GenAI), Large Language Models (LLMs), and AI agents to software quality engineering and test lifecycle automation. The AI Lead Engineer will be responsible for designing and implementing AI-driven solutions to enhance the testing process, analyze requirements, generate test cases, identify and classify defects, and ensure the quality of multilingual and localized content. The position also involves developing AI-assisted checks for accessibility standards and integrating these solutions within CI/CD pipelines. The role requires strong technical expertise in AI/ML concepts, programming languages like Python and Java, and various automation frameworks. The Lead Engineer will also define the AI-QE Solution architecture, technical roadmap, and lead technical discussions with stakeholders to translate business problems into scalable AI solutions.
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.
- Experience 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.
- 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.
Responsibilities
- Design and generate test scenarios, test cases, and test data from requirements, user stories, specifications, API contracts, and technical documentation.
- Build solutions that analyze requirements for functional gaps, ambiguity, traceability, risk, and test coverage.
- Design multi-agent workflows for requirement analysis, test generation, defect analysis, validation, and quality intelligence.
- Develop AI-assisted mechanisms for defect identification, classification, deduplication, severity assessment, root-cause analysis, and automated defect filing.
- Develop AI/LLM-based validation for multilingual and localized content, including translation accuracy, formatting, connectivity, truncation, and content consistency.
- Build AI-assisted automated checks for accessibility violations across web experiences, adhering to standards like WCAG 2.2.
- Integrate automation frameworks, API/UI testing, CI/CD, test orchestration, and reporting.
- Process embeddings, vector databases, RAG, knowledge bases, structured/unstructured data, and enterprise content.
- Define the AI-QE Solution architecture, technical roadmap, reusable accelerators, engineering standards, and measurable business outcomes.
- Lead technical discussions with QE, engineering, product, and client stakeholders.
- Translate business problems into scalable AI solutions.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
