Associate Product Software Engineer - Systems Engineer in Test

Wolters Kluwer•Kennesaw, GA

4d•Onsite

About The Position

Join our innovative team as an Associate Product Software Engineer, where you'll have the opportunity to work with cutting‑edge technologies to build, automate, and integrate software solutions that support product quality and delivery. Your role will focus on developing and maintaining automated testing solutions and integrating them into CI/CD pipelines to improve software quality, reliability, and delivery confidence across our product portfolio, contributing directly to the success and satisfaction of our users.

Requirements

Software Engineering: The ability to design, develop, and maintain software systems and applications by applying principles and techniques of computer science, engineering, and mathematical analysis. This includes understanding user requirements, creating and testing software, and resolving software‑related issues.
Software Development: The ability to design, write, test, and implement software programs, applications, and systems, including familiarity with programming languages, software architecture, and testing approaches.
Programming: The ability to design, write, test, debug, and maintain code using languages such as Python, Java, or C++.
Problem Solving: The ability to analyze complex problems, identify possible approaches, and implement effective solutions.
Analysis: The ability to break down complex systems or issues and understand how components interact.
Testing: The ability to evaluate software systems and processes to identify defects and ensure quality and functionality.
Agile: Familiarity with agile principles emphasizing adaptability, continuous improvement, and iterative delivery.
Source Code Repository: The ability to use source code repositories to manage changes, collaborate with others, and participate in branching and merging workflows.
Relational Database: The ability to work with relational databases, including basic SQL usage and understanding of data relationships.
Advanced Technology Adoption and Utilization: AI Tool Proficiency for basic coding, debugging, and documentation AI Output Validation to verify correctness and functionality Responsible AI Usage in accordance with organizational guidelines Basic Agent Usage for routine development and automation tasks

Responsibilities

Learning, implementation, and execution of well‑defined tasks are central to this position under appropriate technical guidance. Autonomy and responsibility are expected to increase over time as skills, experience, and familiarity grow within our application domains, with growth supported through mentorship, review, and established engineering practices.
Automated Test Development: Assist in designing, coding, and maintaining automated unit, integration, functional, smoke, regression, and load tests.
Test Integration: Support the integration of automated tests into continuous integration and continuous delivery (CI/CD) pipelines to ensure automated validation from pull request through deployment.
Test Code Engineering: Write and maintain test code that follows established coding standards, patterns, and best practices, treating test software as production‑quality code.
Defect Detection and Analysis: Identify, log, and assist in analyzing software defects surfaced through automated test results, logs, and metrics.
Collaboration Across Teams: Work collaboratively with software engineers, quality assurance engineers, DevOps engineers, and load test engineers to support an automated, end‑to‑end SDLC.
Shift‑Left Testing Support: Assist in developing and maintaining testing assets alongside feature development to ensure testing occurs early in the development lifecycle.
Version Control and Code Review: Use source control systems to manage test code changes and participate in code reviews to ensure correctness and maintainability.
Debugging and Troubleshooting: Aid in debugging test failures, automation issues, pipeline problems, and environment‑related failures.
Requirements and System Understanding: Develop an understanding of application behavior, system requirements, and non‑functional expectations such as performance, availability, and reliability.
Quality Metrics and Coverage: Support efforts to improve test coverage, execution reliability, and confidence metrics across a large application portfolio.
Learning and Skill Development: Continuously learn automated testing methodologies, tools, frameworks, CI/CD practices, and AI‑assisted development techniques supported by the organization.