Description
About us:
Where elite tech talent meets world-class opportunities!
At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.
AI & ML Professionals
Requirements
Job Description – Generative AI Tester (5+ Years Experience)
Role Overview
Generative AI Tester 2–3 years focused on Generative AI systems
Key Responsibilities
- Collaborate with product, data science, and engineering teams to understand AI use cases and define test strategies.
- Design and execute test cases for LLM-based features such as summarization, classification, conversational flows, and content generation.
- Validate model outputs for factual accuracy, tone, relevance, and compliance with domain-specific standards.
- Develop automated test scripts and frameworks for prompt-response validation and regression testing.
- Evaluate ML models using metrics like precision, recall, F1-score, and domain-specific thresholds.
- Conduct integration testing across cloud platforms (e.g., AWS, Azure, GCP) and data environments (e.g., Snowflake, Databricks).
- Document test results, anomalies, and improvement suggestions in structured formats.
- Ensure ethical AI practices and compliance with data governance policies.
Required Skills & Experience
- 5+ years in software testing, QA, or data validation roles.
- 2–3 years hands-on experience testingGenerative AI models(e.g., GPT, LLaMA, Claude).
- Strong proficiency inPythonand experience with ML testing tools or frameworks.
- Familiarity with cloud platforms (AWS, Azure, GCP) and data engineering environments (Snowflake, Databricks).
- Understanding of ML workflows including time series, regression, classification, and neural networks.
- Excellent communication skills and ability to drive cross-functional discussions with ownership.
Preferred Qualifications
- Exposure to domain-specific AI applications (e.g., pharma, healthcare, finance).
- Experience with prompt engineering and LLM evaluation frameworks.
- Knowledge of ethical AI principles and regulatory compliance (e.g., HIPAA, GDPR).