Urgently needed for
QA Engineer-Artificial Intelligence
Company: Korn Ferry
- Test Planning & Execution: Develop and implement test strategies, detailed test plans, and test cases tailored to AI, ML, and GenAI solutions
- Quality Assurance & UAT: Conduct thorough Functional, UI, and API testing, including GenAI output quality, hallucination detection, and user acceptance testing to ensure optimal application performance
- Collaboration: Work closely with data scientists, software developers, engineers, and project managers to validate algorithms and integrate QA best practices into development processes
- Automation & Optimization: Implement automation testing frameworks to optimize testing efforts, including automated GenAI evaluation workflows
- Data Integrity & Bias Detection: Verify training data integrity, perform bias detection, and conduct prompt-response validations for AI and GenAI model training
- AI Inter-Rater Reliability: Review and verify AI-generated outputs for consistency and accuracy. Collaborate with AI/ML engineers to enhance automated evaluation systems and pipelines
- Documentation & Reporting: Document test results, identify defects, collaborate to resolve issues, and prepare comprehensive reports with actionable insights for continuous improvement
- Compliance & Best Practices: Ensure adherence to industry standards, regulatory requirements, and Acentra Health standards around ethical and safe AI usage
- Continuous Improvement: Stay current with emerging AI testing methodologies and tools; contribute to evolving QA processes and strategies
- Read, understand, and adhere to all corporate policies including policies related to HIPAA and its Privacy and Security Rules
The list of accountabilities is not intended to be all-inclusive and may be expanded to include other education- and experience-related duties that management may deem necessary from time to time.
QualificationsRequired QualificationsEducation:
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent work experience will be considered
Experience:
- 3+ years of core quality assurance experience (preferably at the enterprise level, managing large scale projects), with a strong background in traditional QA and UAT methodologies
- Exposure to AI/ML: some experience in AI or Machine Learning (ML)
- Proficiency in RESTful APIs and testing tools such as Postman, specifically for testing GenAI model APIs like OpenAI and Hugging Face
- Experience verifying training data integrity, bias detection, and prompt-response validation for AI models
- Familiarity with data annotation tools, and quality control processes
- Demonstrated experience in testing complex software applications
- Proven experience designing, documenting, and executing comprehensive test plans for AI-driven products
- Strong analytical thinking, attention to detail, excellent communication skills, and the ability to thrive in a fast-paced, cross-functional team environment
Technical Skills:
- Strong experience with QA tools and frameworks like PyTest, Selenium, or JUnit
- Solid knowledge of software development life cycle (SDLC) and agile methodologies
- Understanding of AI and ML technologies
- Solid knowledge of Python, with experience or knowledge in Gen AI libraries like LangChain and LlamaIndex (preferred)
- Familiarity with data annotation tools and quality control processes for GenAI-specific tasks
- Knowledge in testing AI, ML, and Generative AI outputs, including Functional, UI, and API testing
- Knowledge of GenAI-specific annotation for RAG and LLM fine-tuning
Soft Skills:
- Excellent analytical and problem-solving skills with keen attention to detail
- Strong communication and collaboration skills, with the ability to explain complex technical issues to diverse audiences
- Ability to work effectively in a fast-paced, cross-functional team environment
Preferred Qualifications
- Experience with GenAI model evaluation metrics such as perplexity and BLEU
- Expereince with Gen AI evaluation frameworks like RAGAS, and GenAI concepts, algorithms, and output validation techniques
- Experience in healthcare technology or data analytics environments
- Familiarity with regulatory and ethical standards related to AI and healthcare solutions
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Skills Required
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Education & Work ExperienceTitle QA EngineerLocation McLean, VAClient Industry HealthcareCompensation $60-70/hrRef ID 1681715
Expected salary: $60 – 70 per hour
Location: McLean, VA
Job date: Sat, 14 Jun 2025 23:58:31 GMT
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