Job Description

We are seeking a Senior Java Automation Test Engineer to build scalable Java and Selenium automation and strengthen API testing with CI/CD integration. You will shape framework architecture, expand REST/SOAP automation with robust XML/JSON validation, and enable fast feedback through Jenkins and GitHub Actions. Use Generative AI and Agentic AI to streamline testing workflows.

Responsibilities

Plan, implement, evolve, and maintain scalable Java automation frameworks
Create dependable UI automation leveraging Selenium
Lead architecture decisions for frameworks with emphasis on reuse, scalability, and maintainability
Apply parallel execution strategies and improve execution times across browsers and platforms
Build shared utilities, reusable libraries, and framework extensions
Develop API automation solutions that support REST and SOAP services
Validate XML and JSON payloads through serialization and deserialization methods
Configure authentication and authorization patterns including Basic Authentication, Bearer Tokens, OAuth, and NTLM
Supervise session management and conduct API integration testing
Conduct code reviews and ensure clean coding discipline is followed
Define and enforce coding standards, branching approaches, and version control practices
Integrate automation suites with CI/CD pipelines using Jenkins and GitHub Actions
Build AI-driven capabilities for automated test case creation, script generation, code review support, and API-based automation workflows

Requirements

6–9 years of hands-on test automation experience
Strong Java proficiency with Object-Oriented Programming fundamentals: classes, objects, inheritance, polymorphism, encapsulation, and abstraction
Deep experience designing scalable test automation frameworks and working with Selenium
Demonstrated capability in REST and SOAP API automation, including XML and JSON payload validation
Sound knowledge of software design patterns such as Singleton, Factory, and Decorator
Experience applying Page Object Model and Page Factory approaches
Experience integrating CI/CD and DevOps workflows using Jenkins and GitHub Actions, including static code analysis and quality gate implementation
Hands-on experience with Large Language Models like GitHub Copilot, Claude, and Cursor
Solid understanding of prompt engineering, context window management, and tokenization
Working knowledge of model selection methods, embeddings, and vector databases for semantic search use cases
Ability to design and build AI agents and AI-assisted engineering solutions using OpenAI Assistants, GitHub Copilot, and Claude
Understanding of similarity search techniques and retrieval mechanisms

Nice to have

Experience with agentic workflows and collaborative multi-agent systems for end-to-end testing, automated reporting, and workflow coordination
Familiarity with Retrieval-Augmented Generation architectures and integrating LLMs with enterprise knowledge sources
Understanding of Model Context Protocol concepts and related frameworks
Knowledge of Attention Mechanisms and Transformer-based model design