AI Lead Engineer

Kaleidoscope Innovation

$150K — $180K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong understanding of GenAI, LLMs, and agentic AI applications in software quality engineering.
  • Expertise in designing test scenarios, cases, and data from various requirements and documentation.
  • Proven experience in analyzing requirements for functional gaps and risk assessment.
  • Hands-on skills in creating multi-agent workflows for defect analysis and quality validation.
  • Experience in AI-assisted defect identification and classification mechanisms.
  • Familiarity with validation of multilingual content and accessibility standards such as WCAG 2.2.
  • Proficient in Python and Java/TypeScript, with capabilities in API integration.

Responsibilities

  • Apply GenAI and LLMs to automate software quality engineering processes.
  • Design and generate comprehensive test scenarios and data from technical specifications.
  • Build solutions to analyze functional gaps, traceability, and coverage risks.
  • Create workflows for requirement analysis and quality intelligence using multi-agent systems.
  • Develop AI-based mechanisms for efficient defect management and automated filing.
  • Ensure validation of multilingual content against localization standards.
  • Lead technical discussions and translate complex problems into AI solutions.

Benefits

  • Hybrid work arrangement, allowing flexibility between remote and in-office work.
  • Opportunity to work at the forefront of AI and software quality engineering.
  • Collaborative environment focused on innovative technology solutions.
  • Development and advancement opportunities in AI technologies.
Full Job Description
*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


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