automation qa

EPAM provides digital platform engineering and software development services, focusing on cloud, automation, and AI-driven systems to ensure the reliability and safety of next-generation applications.

• Analyze requirements and architecture to create comprehensive test plans, cases, and data sets across functional, integration, regression, and exploratory testing;
• Design and maintain automation frameworks using tools such as Cypress, Playwright, Selenium, JMeter, and Gatling;
• Develop and integrate testing tools into CI/CD pipelines to boost engineering productivity;
• Build observability and telemetry solutions for real-time quality monitoring;
• Identify and automate repetitive tasks to reduce manual testing effort;
• Manage defect lifecycle from reproduction and isolation to documentation and prioritization;
• Apply AI-assisted workflows for test generation, code review, and defect triage while validating AI outputs;
• Design and execute targeted testing for AI/LLM-powered features, including safety and reliability checks;
• Collaborate with developers for quality-first practices across the SDLC and provide leadership in quality strategy;
• Work within an agile delivery model, contributing to process improvements and mentoring team members.

• Strong experience in software quality assurance covering UI/black-box testing and white-box techniques;
• Proficiency in at least one programming language (Java, Python, Scala, or TypeScript);
• Hands-on experience with automation tools (e.g., Cypress, Playwright, Selenium);
• Understanding of SDLC, STLC, and agile practices;
• Proven experience with CI/CD systems (e.g., GitLab, Jenkins, Azure DevOps, Argo CD);
• Knowledge of cloud services and container platforms (AWS, Azure, GCP, Kubernetes, Docker);
• Familiarity with observability tools (Splunk, Grafana, Prometheus, Datadog);
• Practical experience with AI coding assistants (e.g., GitHub Copilot, Claude Code) for test authoring and debugging;
• Familiarity with testing AI features, including evaluation harnesses, golden-set tests, prompt injection safeguards, and model regression strategies;
• Awareness of responsible AI principles: bias, fairness, privacy, and safety considerations;
• Experience designing and validating prompts, LLM workflows, and automation environments with AI integration;
• Excellent communication, analytical, and problem-solving skills;
• Nice to have: experience with performance testing (e.g., Gatling, JMeter), prior leadership experience in QA teams or test strategy definition, experience in highly regulated or data-sensitive environments.

• No conditions specified