Manager, Software Quality Assurance

We are seeking an experienced Manager II (M2) Software Automation Engineer to lead the design, implementation, and adoption of next-generation Quality Engineering solutions powered by Agentic AI , intelligent automation, and modern software testing practices. This role combines deep technical expertise with leadership responsibilities to modernize testing strategies, drive AI-assisted automation, and mentor engineering teams in building scalable, resilient, and intelligent quality solutions.

The ideal candidate has extensive experience in automation frameworks, cloud-native applications, AI/LLM technologies, and software engineering while leading cross-functional teams in delivering high-quality enterprise software.

Key Responsibilities

Technical Leadership Lead the architecture, design, and implementation of enterprise automation frameworks using modern technologies. Drive adoption of Agentic AI solutions for autonomous test generation, maintenance, defect triage, root cause analysis, and release validation. Establish engineering standards, best practices, and governance for automation and AI-assisted testing.

Design scalable CI/CD quality gates supporting continuous delivery. Develop and implement comprehensive test strategies. Lead framework modernization initiatives from legacy automation to AI-powered solutions. Oversee the execution of automated and manual testing and generate traceable reporting. Prepare and present quality reports to senior management Collaborate with cross-functional teams to improve product quality.

Define and monitor quality metrics and key performance indicators. Conduct performance reviews and provide career development opportunities. Agentic AI & Intelligent Automation Design and implement AI agents for: Automated test case generation Self-healing test automation Intelligent regression selection Failure analysis Root cause identification Requirement-to-test traceability Defect summarization Test data generation Risk-based testing Integrate Large Language Models (LLMs) into automation workflows.

Evaluate and implement Agentic AI platforms, MCP (Model Context Protocol), prompt engineering, and Retrieval-Augmented Generation (RAG). Optimize token usage, AI performance, governance, and cost management. Automation Engineering Develop scalable automation solutions for: UI API Integration Performance Database End-to-End testing Build automation using: Playwright/Selenium Java/C# REST Assured API Postman Software Engineering Apply SOLID principles and clean architecture.

Build cloud-native automation services and APIs. Develop reusable testing utilities and AI integrations. Cloud & DevOps Integrate automation into CI/CD pipelines. Deploy automation services on: Azure AWS Monitor quality metrics using Grafana, ADO Required Qualifications Education Bachelor's degree in Computer Science, Software Engineering, or related field.

Master's degree preferred. Experience 8–12+ years of software engineering or Quality Engineering experience. 5+ years designing enterprise automation frameworks. 3+ years leading engineering teams or technical initiatives. Experience implementing AI-assisted software development or testing solutions. Experience working within Agile/Scrum environments.

Our Interview Practices To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant.

To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process. Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.