QA - API and UI Automation at Epicor Software Corporation

📍 Job Overview

Job Title: QA - API and UI Automation
Company: Epicor Software Corporation
Location: Bangalore, Karnataka, India
Job Type: FULL_TIME
Category: Quality Assurance Operations / Software Development Operations
Date Posted: 2025-07-24T00:00:00
Experience Level: Mid-Level (3-5 years)
Remote Status: Hybrid

🚀 Role Summary

This role is for a Product QA Developer with a focus on full-stack automation, integrating modern technologies like AI/ML and LLMs into Quality Assurance processes.
Responsibilities include designing and developing QA tools, enhancing test automation, and improving defect analysis and reporting through intelligent testing techniques.
The position requires collaboration with development, product, and QA teams to deliver high-quality, testable, and maintainable software solutions.
A key aspect involves supporting CI/CD pipelines with advanced automation to boost efficiency and test coverage.

📝 Enhancement Note: While the title specifies "QA - API and UI Automation," the description strongly indicates a hybrid role blending traditional QA automation with AI/ML integration for enhanced testing capabilities. This suggests a move towards "Quality Engineering" or "Software Development in Test" with a forward-thinking approach to automation. The emphasis on AI/ML implies a need for candidates who can not only build robust automation frameworks but also explore and implement intelligent solutions for quality assurance.

📈 Primary Responsibilities

Analyze software requirements and design comprehensive full-stack QA automation tools, encompassing frontend, backend, and API layers.
Develop and integrate AI/ML-powered tools to significantly enhance test automation efficiency, refine defect analysis, and improve the accuracy of QA reporting.
Support and optimize the Continuous Integration/Continuous Deployment (CI/CD) pipeline by implementing intelligent testing strategies that boost overall efficiency and broaden test coverage.
Design, develop, and maintain internal web applications, backend services, and robust automation frameworks to effectively support and streamline QA efforts.
Gain exposure and practical experience working with containerization technologies such as Docker and other container orchestration platforms.
Collaborate effectively with cross-functional teams, including Product Management, Development, and fellow QA Engineers, to gather detailed requirements and consistently deliver high-quality software solutions.
Actively participate in code reviews, providing constructive feedback and proposing standards to ensure optimal testability and maintainability of the codebase.
Debug and troubleshoot issues methodically across the entire technology stack, including databases, APIs, and user interfaces.
Stay updated with emerging trends and advancements in AI/ML, automation technologies, and testing tools, proactively bringing innovative solutions to enhance QA and automation practices.

📝 Enhancement Note: The responsibilities highlight a significant pivot towards integrating AI/ML into QA. This isn't just about building traditional automation; it's about leveraging advanced technologies to create smarter testing processes. Candidates should be prepared to discuss how they would approach AI-driven defect prediction, test case optimization, or even natural language processing for test script generation.

🎓 Skills & Qualifications

Education:

Bachelor’s degree in Computer Science, Software Engineering, or a closely related technical field.

Experience:

3 to 5 years of professional software development and quality assurance experience.
Proven experience in designing, developing, and maintaining automation frameworks for both API and UI testing.
Demonstrated understanding of software testing methodologies, principles, and best practices, including test case design, execution, and defect management.

Required Skills:

Basic understanding of non-functional requirements (e.g., security, accessibility, performance) and how to incorporate them into testing strategies.
Hands-on experience with automation frameworks such as Selenium, WebdriverIO (WDIO), Cypress, or Playwright.
Solid grasp of software testing methodologies and best practices, including test planning, strategy, and execution.
Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse technical teams.
Proficiency in writing and maintaining unit tests using relevant frameworks (e.g., JUnit, PyTest, Mocha, Jest).
Experience in API development and testing, including proficiency with tools and techniques for API integration and validation.

Preferred Skills:

Proficient understanding of software development principles, including object-oriented programming (OOP) and common design patterns.
Experience with frontend development technologies (e.g., Angular, React, Vue.js) and backend development technologies (e.g., Node.js, Python, .NET).
Understanding of DevOps principles, CI/CD processes, and related tools such as Jenkins, GitHub Actions, or Azure DevOps.
Hands-on experience working with various database systems, including both Relational Database Management Systems (RDBMS) and NoSQL databases.
Exposure to and familiarity with cloud platforms like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).

📝 Enhancement Note: The "Must Have" section includes "API development and testing along with unit testing," which is a critical skill for modern QA roles. The "Could set you apart" section indicates a preference for full-stack development capabilities, suggesting that candidates with a strong development background who can also perform QA automation will have a significant advantage. This role leans towards "Software Development Engineer in Test" (SDET) or "Quality Engineering."

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

Showcase practical examples of automation frameworks developed for API and UI testing, demonstrating proficiency with tools like Selenium, Cypress, or Playwright.
Include case studies or project examples where AI/ML concepts were applied to enhance QA processes, such as intelligent defect analysis, automated test case generation, or performance anomaly detection.
Provide examples of how you have integrated automation into CI/CD pipelines, illustrating the impact on deployment frequency and code quality.
Demonstrate experience in building or contributing to internal QA tools, web applications, or backend services that improved team efficiency or testing capabilities.
Evidence of working with containerization technologies (Docker) in a development or testing context.

Process Documentation:

Documentation of test automation strategies, including approach, scope, and tooling selection for API and UI testing.
Examples of process improvements implemented in CI/CD pipelines or defect management workflows.
Records of code reviews performed and contributions to coding standards for testability and maintainability.
Methodologies used for debugging and troubleshooting across different layers of the application stack.

📝 Enhancement Note: Given the emphasis on AI/ML integration and full-stack development, a portfolio should ideally highlight projects that demonstrate not just automation execution but also the design and development of automation solutions. Examples of custom scripts, framework components, or tools built to solve specific QA challenges would be highly valuable.

💵 Compensation & Benefits

Salary Range:

Based on industry benchmarks for Mid-Level QA Automation Engineers with 3-5 years of experience in Bangalore, India, a competitive salary range is estimated to be between ₹8,00,000 to ₹15,00,000 per annum. This range accounts for the specialized skills in AI/ML integration and full-stack development capabilities.

Benefits:

Health and Wellness: Comprehensive health and wellness benefits designed to support overall well-being.
Internal Mobility: Opportunities for mentorship, continuing education, and focused career goal setting, with a strong emphasis on internal role fulfillment (25% of positions filled internally).
Career Development: Access to free LinkedIn Learning licenses and participation in a dedicated Mentoring Program to enhance personal and professional development.
Education Support: Geographically specific programs available to help balance the cost of education with the benefits of continued learning and personal development.
Inclusive Workplace: Opportunity to collaborate with a diverse, global team in an inclusive environment that fosters innovation and partnership.
Work-Life Balance: Policies built on mutual trust and support, encouraging employees to take time off to rest, recharge, and reconnect.
Global Mobility: Comprehensive support provided for international relocations and permanent residency processes.

Working Hours:

Standard full-time working hours, typically around 40 hours per week, with potential for flexibility given the hybrid work arrangement.

📝 Enhancement Note: The salary estimate is based on research for similar roles in Bangalore, India, considering the specific technical requirements including AI/ML and full-stack development. Benefits are directly pulled from the job description's "Competitive Pay & Benefits" section, highlighting Epicor's commitment to employee growth and well-being.

🎯 Team & Company Context

🏢 Company Culture

Industry: Enterprise Software (ERP solutions)
Company Size: Over 5,000 employees (as per job description)
Founded: Epicor has a history dating back to 1972, indicating a well-established company with significant market presence and experience in delivering business solutions.

Team Structure:

The QA team is likely integrated within product development teams, working closely with developers and product owners.
Reporting structure would typically involve a QA Lead or Manager, with direct reports contributing to specific product lines or features.
Cross-functional collaboration is a key aspect, involving close partnerships with Product Management for requirement analysis and Development teams for implementation and issue resolution.

Methodology:

Data-driven approaches are expected, leveraging analytics from testing and AI/ML insights to drive quality improvements.
Workflow planning and optimization are critical, especially in integrating new technologies into existing QA processes.
Automation and efficiency practices are central to the role, aiming to accelerate release cycles and improve product robustness.

Company Website: Epicor Software Corporation (Inferred from domain and company name)

📝 Enhancement Note: Epicor's focus on "data, AI, and cognitive ERP" suggests a company culture that values technological innovation and forward-thinking solutions. The mention of "making, moving, and selling the things the world needs" points to a mission-driven organization that supports essential businesses. The dual emphasis on "Proactive, Proud, Partners" highlights a culture that values initiative, quality of work, and collaborative relationships.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a Mid-Level or early Senior level within the Quality Assurance/Software Development discipline. It offers a trajectory beyond traditional manual or basic automation testing, venturing into cutting-edge areas like AI/ML in QA.

Reporting Structure: The role likely reports to a QA Manager or Lead who oversees the automation and testing efforts for specific product modules or the entire product suite. Collaboration with Product Managers and Development Leads is also a key part of the ecosystem.

Operations Impact: This role directly impacts the efficiency and effectiveness of the software development lifecycle. By enhancing test automation with AI/ML, it contributes to faster release cycles, reduced defect leakage, improved product quality, and ultimately, better customer satisfaction and business outcomes for Epicor's clients.

Growth Opportunities:

Operations Skill Advancement: Deepen expertise in AI/ML applications for QA, advanced automation techniques, and full-stack development within a corporate environment.
Industry Exposure: Gain experience with enterprise-level ERP software, understanding the complexities and quality demands of business-critical applications.
Leadership Potential: Grow into a Senior QA Engineer, Automation Architect, or Team Lead role, mentoring junior engineers and driving strategic QA initiatives. Opportunities for specialization in AI/ML for QA are also probable.

📝 Enhancement Note: The role offers a strong growth path for QA professionals looking to specialize in advanced automation and AI/ML. The company's emphasis on internal mobility and career development suggests a structured approach to employee growth, making it an attractive position for those seeking long-term career progression within the operations and engineering space.

🌐 Work Environment

Office Type: The job posting indicates a "Hybrid" work arrangement, suggesting a mix of remote work and in-office presence. This implies a modern office setup designed to facilitate both individual focused work and collaborative team activities.

Office Location(s): The primary location is specified as Bangalore, India.

Workspace Context:

The workspace is expected to be collaborative, encouraging interaction with developers, product owners, and other QA engineers.
Access to necessary tools and technology, including development environments, testing platforms, and collaboration software, will be provided to support the hybrid work model.
Opportunities for team interaction will likely occur during planned in-office days for brainstorming, code reviews, and project discussions.

Work Schedule:

Standard working hours are expected for a full-time position, likely aligning with Indian business hours (Asia/Kolkata timezone).
The hybrid nature may offer some flexibility in structuring the work week, balancing remote focus time with in-office collaboration.

📝 Enhancement Note: The "Hybrid" work arrangement means candidates should be comfortable with a blend of remote and in-office work, and possess the self-discipline for remote productivity while also being adept at in-person collaboration.

📄 Application & Portfolio Review Process

Interview Process:

Initial Screening: A recruiter or hiring manager will likely conduct an initial screening to assess basic qualifications, experience, and cultural fit.
Technical Interview(s): Expect one or more technical interviews focusing on core QA principles, automation frameworks (Selenium, Cypress, etc.), API testing concepts, programming skills (Python, Java, etc.), and understanding of AI/ML applications in QA.
Coding/Automation Challenge: A practical coding or automation challenge might be administered to evaluate hands-on skills in developing automated tests or scripts.
System Design/Architecture Discussion: For roles involving framework development, there may be a discussion on designing scalable and maintainable automation solutions.
Behavioral/Situational Interview: Questions assessing problem-solving abilities, teamwork, communication, and how candidates handle specific work scenarios.
Final Interview: Potentially with a senior leader or director, focusing on strategic thinking, alignment with company values, and long-term career aspirations.

Portfolio Review Tips:

Highlight AI/ML Integration: Showcase specific projects where AI/ML was used to solve QA problems. Detail the approach, tools used, and measurable impact.
Demonstrate Framework Development: Provide examples of custom automation frameworks or significant contributions to existing ones. Explain design choices and architectural patterns.
Showcase Full-Stack Capabilities: Include examples of backend service testing, API automation, and any frontend development or tooling you've built.
Quantify Impact: Use metrics to demonstrate the value of your work – e.g., reduction in execution time, increase in test coverage, decrease in escaped defects.
Code Quality: Ensure any code samples or links to repositories are well-organized, commented, and follow best practices.
Clarity and Conciseness: Clearly articulate the problem, your solution, and the results for each project.

Challenge Preparation:

Core Concepts: Brush up on data structures, algorithms, object-oriented programming, and common design patterns.
Automation Tools: Practice writing automated tests using Selenium, Cypress, or Playwright. Be ready to explain your choices.
API Testing: Understand RESTful principles, HTTP methods, status codes, and how to automate API tests using tools like Postman or code libraries.
AI/ML Fundamentals: Familiarize yourself with basic AI/ML concepts, common algorithms, and how they can be applied to QA tasks (e.g., anomaly detection, predictive analytics for defects).
CI/CD Basics: Understand the principles of CI/CD and how automated testing fits into the pipeline.

📝 Enhancement Note: The interview process is expected to be rigorous, assessing both foundational QA skills and advanced capabilities in automation and AI/ML. Candidates should prepare to discuss their thought processes for building robust automation solutions and how they leverage data and emerging technologies.

🛠 Tools & Technology Stack

Primary Tools:

Automation Frameworks: Selenium, WebdriverIO (WDIO), Cypress, Playwright (for UI and API automation).
Programming Languages: Python, Node.js, .NET (for backend development and scripting).
Frontend Technologies: Angular, React, Vue.js (for understanding and testing applications).
API Testing Tools: Postman, Swagger, or custom API testing scripts.
Containerization: Docker, Kubernetes (or similar).

Analytics & Reporting:

CI/CD Tools: Jenkins, GitHub Actions, Azure DevOps (for pipeline integration).
Version Control: Git (essential for code management).
Test Management Tools: Jira (likely for defect tracking and test case management), TestRail, or similar.

CRM & Automation:

While not explicitly mentioned as a primary focus for this role, understanding CRM systems (like Salesforce) and general automation platforms could be beneficial for context, especially in an ERP environment.

📝 Enhancement Note: Proficiency in at least one major UI automation framework and strong API testing skills are non-negotiable. Experience with Python or Node.js is highly advantageous due to their prevalence in scripting and backend development. Familiarity with cloud platforms and DevOps tools is a significant plus.

👥 Team Culture & Values

Operations Values:

Innovation: Encouraging the exploration and implementation of cutting-edge technologies like AI/ML to drive QA advancements.
Collaboration: Fostering a team environment where cross-functional communication and shared problem-solving are paramount.
Quality Focus: A deep commitment to delivering high-quality products through rigorous testing and proactive defect prevention.
Efficiency: Driving continuous improvement in processes and automation to optimize resource utilization and accelerate delivery.
Proactive Problem Solving: Addressing challenges head-on and seeking innovative solutions rather than just identifying issues.

Collaboration Style:

Expect a highly collaborative style, working closely with developers to ensure code is testable and with product owners to align testing efforts with business requirements.
Regular participation in team meetings, code reviews, and knowledge-sharing sessions is anticipated.
Feedback is likely encouraged, promoting a culture of continuous learning and process refinement within the QA and development teams.

📝 Enhancement Note: The company's stated values of "Proactive, Proud, Partners" suggest an environment where initiative, accountability, and strong working relationships are highly valued. Candidates who align with these principles will likely thrive.

⚡ Challenges & Growth Opportunities

Challenges:

Integrating AI/ML into Existing QA: The primary challenge will be to effectively incorporate AI/ML technologies into current QA workflows and automation frameworks, requiring a blend of technical skill and strategic thinking.
Keeping Pace with Technology: The rapidly evolving landscape of AI/ML and automation tools necessitates continuous learning and adaptation to stay effective.
Cross-Functional Dependencies: Ensuring seamless collaboration and communication across different teams (Development, Product) to achieve quality goals.
Balancing Innovation with Stability: Implementing new AI-driven testing approaches while ensuring the stability and reliability of existing automation suites.

Learning & Development Opportunities:

Specialization in AI/ML for QA: Opportunities to become an expert in applying AI/ML techniques to automate and optimize testing processes.
Full-Stack Development Skills: Enhancing frontend and backend development skills through practical application and team collaboration.
Industry Best Practices: Learning from experienced engineers and adopting industry-leading practices in software quality assurance and automation.
Mentorship Programs: Access to mentorship from senior engineers and leaders within Epicor to guide career growth and skill development.

📝 Enhancement Note: This role presents a significant opportunity to work at the forefront of QA innovation. The challenges are directly linked to the growth potential, making it an exciting prospect for ambitious QA professionals.

💡 Interview Preparation

Strategy Questions:

How would you approach designing an API automation framework from scratch? What key components would it include?
Describe a situation where you used AI/ML to improve a QA process. What was the problem, your solution, and the measurable outcome?
How do you ensure testability and maintainability in the code you automate? What are your code review best practices for QA engineers?
How would you contribute to a CI/CD pipeline to maximize the value of automated testing?
Imagine you found a critical bug just before a release. How would you communicate this to stakeholders and what steps would you take?

Company & Culture Questions:

What do you know about Epicor and its products?
How do you align with Epicor's values of being Proactive, Proud, and Partners?
Describe your ideal team environment and how you contribute to it.
How do you handle working with tight deadlines or changing priorities?

Portfolio Presentation Strategy:

Structure: Organize your portfolio by project or by skill area (e.g., API Automation, UI Automation, AI/ML Integration, Framework Development).
Narrative: For each project, clearly state the problem, your role, the technical approach used, the tools and technologies involved, and the quantifiable results or impact.
Demonstration: Be prepared to walk through code samples, show live demos of automated tests, or explain the architecture of frameworks you've built.
AI/ML Focus: Explicitly highlight any AI/ML components, explaining the algorithms used and the benefits achieved.
Conciseness: Keep explanations clear and to the point, focusing on the most impactful aspects of your work.

📝 Enhancement Note: Prepare specific examples that showcase your ability to not only automate but also to innovate and contribute to the broader development process. Quantifiable results are key to demonstrating impact.

📌 Application Steps

To apply for this operations position:

Submit your application through the provided Workday job portal link.
Portfolio Customization: Review your existing projects and select those that best demonstrate your skills in API automation, UI automation, AI/ML integration in QA, and CI/CD pipeline contributions. Prepare concise summaries and metrics for each.
Resume Optimization: Tailor your resume to highlight keywords from the job description, such as "AI/ML," "LLMs," "Automation Frameworks," "API Development," "CI/CD," and specific programming languages or tools mentioned. Quantify achievements wherever possible.
Interview Preparation: Practice answering behavioral and technical questions, focusing on concrete examples from your experience. Prepare to discuss your approach to automation challenges and your understanding of AI in QA. Rehearse presenting your portfolio.
Company Research: Familiarize yourself with Epicor's products, mission, and company culture. Understand how your skills and career aspirations align with the company's direction, particularly its focus on AI and digital transformation in ERP.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

QA - API and UI Automation