Lead Java Automation Test Engineer with AI

EPAM Systems; Bengaluru; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

EPAM Systems is seeking a Lead Java Automation Test Engineer to architect and scale AI-enhanced test automation, covering Java, Selenium, and API testing. You will guide teams, shape frameworks, and drive CI/CD integration to shorten delivery cycles.

Ideal candidates will have extensive experience in Java-based automation, API testing, and DevOps practices, with a focus on scalable, maintainable solutions and AI-assisted testing workflows.

Qualifications

• 9–14 years in test automation engineering.
• Strong Java, Selenium, and framework design skills.
• Experience with API automation for REST and SOAP.
• CI/CD and DevOps integration with Jenkins and GitHub Actions.
• Familiarity with AI-assisted testing and large language models.
• Knowledge of OOP and design patterns.

Responsibilities

• Architect and maintain scalable Java-based automation frameworks.
• Build Selenium-based automation and API automation for REST/SOAP.
• Guide architecture decisions for scalability and maintainability.
• Integrate automation suites with CI/CD pipelines (Jenkins, GitHub Actions).
• Lead and mentor team members.
• Implement AI-powered test case creation and code review support.
• Ensure coding standards and QA best practices.
• Verify XML/JSON payloads and security schemes.

Skills

Java

Selenium

Test automation

CI/CD

Jenkins

GitHub Actions

API automation

OO design

Tools

Selenium

Jenkins

GitHub Actions

GitHub Copilot

Job description

We're on the hunt for a highly capable Lead Java Automation Test Engineer bringing solid expertise across Java automation frameworks, API testing, CI/CD integration, and cutting-edge AI-powered testing methods. The right candidate will take charge of architecting scalable automation solutions, advancing quality engineering standards, guiding team members, and harnessing Generative AI and Agentic AI capabilities to speed up software testing and delivery cycles.

Responsibilities

• Architect, build, refine, and sustain scalable test automation frameworks built on Java
• Construct dependable automation solutions using Selenium
• Guide framework architecture decisions with an eye toward scalability, maintainability, and reusability
• Roll out parallel execution approaches and fine-tune execution speed across various browsers and platforms
• Build reusable libraries, utility functions, and framework extensions
• Apply solid Object-Oriented Programming concepts, including classes, objects, inheritance, polymorphism, encapsulation, and abstraction
• Architect and build API automation solutions covering both REST and SOAP services
• Verify XML and JSON payload integrity through serialization and deserialization approaches
• Set up authentication and authorization schemes, including Basic Authentication, Bearer Tokens, OAuth, and NTLM
• Manage session handling and conduct API integration testing
• Perform code reviews and uphold clean coding practices
• Define and maintain coding conventions, branching approaches, and version control best practices
• Connect automation suites into CI/CD pipelines through Jenkins and GitHub Actions
• Architect and implement AI-powered solutions supporting automated test case creation, script generation, and code review processes

Requirements

• Between 9 and 14 years of background in test automation engineering
• Strong command of Java, Selenium, and designing test automation frameworks
• Skilled in Object-Oriented Programming principles and design patterns, such as Singleton, Factory, and Decorator
• Familiarity with Page Object Model and Page Factory design approaches
• Capability in API automation covering REST and SOAP services, including XML and JSON validation
• Strong background integrating CI/CD and DevOps practices using Jenkins and GitHub Actions
• Ability to configure static code analysis tools, quality gates, and automation reporting dashboards
• Practical experience working with Large Language Models, such as GitHub Copilot, Claude, and Cursor
• Solid understanding of Prompt Engineering, Context Window Management, and Tokenization concepts
• Working knowledge of embeddings, vector databases, and semantic search implementations
• Background working with AI agents and AI-assisted engineering tools, such as OpenAI Assistants

Nice to have

• Background constructing multi-agent and agentic workflows to support end-to-end testing and workflow coordination
• Familiarity with Retrieval-Augmented Generation architecture and its integration with enterprise knowledge repositories
• Understanding of Model Context Protocol concepts and associated frameworks
• Knowledge of Attention Mechanisms and Transformer-based model design