Job Description
Day to Day
This engineer will be responsible for validating AI-driven applications and data platforms They will design and execute test strategies focused on model accuracy, data integrity, and system performance. Daily work includes building and maintaining automated test frameworks for APIs and data pipelines, performing end-to-end testing of microservices, and validating data across ingestion through model output layers. They will collaborate closely with engineers, data scientists, and product teams to troubleshoot defects, ensure production readiness, and integrate testing into CI/CD workflows. The role also involves contributing to emerging testing practices around AI quality, including model bias, fairness, and monitoring.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
Must Have
5+ years of software testing experience (manual + automation)
Strong programming in Python (preferred) or Java
Hands-on experience with automation frameworks (Selenium, Playwright, PyTest)
API testing experience (Postman, REST Assured)
Solid understanding of SDLC, STLC, and Agile methodologies
Experience integrating tests into CI/CD pipelines (Jenkins, Azure DevOps, GitHub Actions)
Experience testing APIs, microservices, and distributed systems Plusses
Experience testing AI/ML models (model validation, accuracy, performance)
Understanding of AI/ML metrics (precision, recall, F1 score)
Cloud platform experience (AWS, GCP, Azure)
Experience with data/ETL pipeline testing
Performance or load testing experience
Experience working in global/onshore-offshore environments
Exposure to AI risk topics such as bias and fairness
