Jobs → QA & Testing → AI Test Lead

About the Role We are looking for an AI Test Lead to join our team for a 6-month contract. This role focuses on leading AI testing initiatives and ensuring quality across enterprise workflows. Key Responsibilities • Lead testers embedded in delivery pods, assign test work, review automation, and coach AI-assisted testing practices • Partner with Development Leads to ensure technical specifications are testable and that acceptance criteria include measurable verification and rollback conditions • Design and build executable test suites in enterprise test management/automation tooling • Create, refine, and govern AI agents/skills that assist with test scenario generation, test data design, coverage analysis, traceability, defect triage, and regression maintenance • Establish quality gates for agent-generated code and modernization changes Requirements • 7-10 years of QA/SDET/QE experience with strong automation and AI testing skills • Experience with AI Assisted QE, system integration testing • Strong SDET/quality engineering background with hands-on automation of APIs, integrations, UI, and end-to-end enterprise workflows • Demonstrated use of AI/agentic tools to generate, refine, review, or maintain test scenarios and automation • Experience creating regression, system integration coverage for applications with incomplete or outdated test suites • Strong knowledge of test strategy, risk-based testing, test design, traceability, defect management, root-cause analysis, and CI/CD quality gates • Hands-on experience with modern automation tools such as Playwright, Cypress, Selenium, REST/API automation • Working knowledge of Java/.NET application behavior, databases/SQL, APIs, middleware, authentication/authorization, and enterprise integration patterns • Understanding of LDAP and token-based authentication concepts sufficient to design security and role/authorization test scenarios • Ability to evaluate nondeterministic AI outputs with repeatable acceptance criteria, structured evaluation, and human verification • Assess each application's existing test assets, business-critical flows, integrations, data dependencies, security behavior, and regression risk before modernization begins • Reverse-engineer system behavior with developers and AI agents, then create a risk-based system integration and regression strategy where adequate suites do not already exist • Define test coverage for runtime/framework upgrades, dependency changes, OS/middleware changes, database/integration impacts, and LDAP-to-Okta/token-based security changes