Lead Java Automation Test Engineer with AI

EPAM Systems; India; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

EPAM Systems is seeking a Lead Java Automation Test Engineer to design and scale automation frameworks in Java, using Selenium and API testing. You will drive CI/CD integration, mentor teams and explore AI-driven testing approaches.

Candidates should have 9–14 years of experience, strong OOP and design-pattern knowledge, and experience with multi-agent AI workflows and RAG architectures.

Qualifications

• 9–14 years of test automation engineering experience.
• Expertise in Java, Selenium and framework design.
• Strong OOP and design-pattern knowledge.
• Proficiency in API automation for REST/SOAP.
• CI/CD and DevOps integration experience.
• Familiar with AI/LLMs and AI-assisted testing approaches.

Responsibilities

• Design, develop, enhance and maintain scalable test automation frameworks using Java.
• Lead framework architecture decisions focused on scalability and reusability.
• Implement parallel execution strategies across browsers and platforms.
• Develop reusable libraries, utilities and framework extensions.
• Design and implement API automation solutions for REST and SOAP services.
• Integrate automation suites with CI/CD pipelines (Jenkins, GitHub Actions).
• Mentor teams and enforce clean coding standards and reviews.
• Explore AI-driven test case generation and AI-assisted testing workflows.

Skills

Java

Selenium

Test automation framework design

OOP principles

Design patterns

Page Object Model

API automation

CI/CD

DevOps integration

GitHub Actions

Jenkins

Static code analysis

Automation dashboards

AI/LLMs

Prompt engineering

Embeddings

Vector databases

Semantic search

AI agents

Multi-agent workflows

RAG architectures

Transformer architectures

Tools

Selenium

Jenkins

GitHub Actions

Job description

We are seeking a highly skilled Lead Java Automation Test Engineer with strong expertise in Java automation frameworks, API testing, CI/CD integration and modern AI-driven testing practices. The ideal candidate will be responsible for designing scalable automation solutions, driving quality engineering practices, mentoring teams and leveraging Generative AI and Agentic AI technologies to accelerate software testing and delivery.

Responsibilities

• Design, develop, enhance and maintain scalable test automation frameworks using Java
• Build robust automation solutions using Selenium
• Lead framework architecture decisions focused on scalability, maintainability and reusability
• Implement parallel execution strategies and optimize execution times across browsers and platforms
• Develop reusable libraries, utilities and framework extensions
• Apply strong Object-Oriented Programming principles including classes, objects, inheritance, polymorphism, encapsulation and abstraction
• Design and implement API automation solutions for REST and SOAP services
• Validate XML and JSON payloads through serialization and deserialization techniques
• Implement authentication and authorization mechanisms including Basic Authentication, Bearer Tokens, OAuth and NTLM
• Handle session management and API integration testing
• Conduct code reviews and enforce clean coding standards
• Establish and govern coding standards, branching strategies and version control best practices
• Integrate automation suites with CI/CD pipelines using Jenkins and GitHub Actions
• Design and implement AI-driven solutions for automated test case generation, test script generation and code reviews

Requirements

• 9 to 14 years of experience in test automation engineering
• Expertise in Java, Selenium and test automation framework design
• Proficiency in Object-Oriented Programming principles and software design patterns such as Singleton, Factory and Decorator
• Knowledge of Page Object Model and Page Factory
• Skills in API automation for REST and SOAP services including XML and JSON validation
• Competency in CI/CD and DevOps integration using Jenkins and GitHub Actions
• Capability to configure static code analysis, quality gates and automation reporting dashboards
• Hands‑on experience with Large Language Models such as GitHub Copilot, Claude and Cursor
• Understanding of Prompt Engineering, Context Window Management and Tokenization
• Familiarity with embeddings, vector databases and semantic search applications
• Background in AI agents and AI‑assisted engineering using tools such as OpenAI Assistants
• Experience building multi-agent and agentic workflows for end-to-end testing and workflow orchestration
• Knowledge of Retrieval‑Augmented Generation architectures and integration with enterprise knowledge sources
• Understanding of Model Context Protocol concepts and frameworks
• Understanding of Attention Mechanisms and Transformer‑based model architectures