Solutions Architect – QA

About the Role

We are looking for an experienced Solutions Architect – QA to design and implement scalable automation strategies that enable high-quality software delivery. This role is ideal for a seasoned QA professional with deep expertise in automation, proven experience building frameworks, and a forward-looking mindset toward AI-driven testing solutions.

The Solutions Architect – QA will serve as a technical leader, responsible for driving test automation initiatives, setting best practices, and mentoring teams in building robust and efficient testing frameworks.

Key Responsibilities

• Design and architect end-to-end automation solutions covering UI, API, data, and cloud-based systems.
• Build and maintain scalable automation frameworks leveraging design patterns and best practices.
• Evaluate, implement, and optimize licensed and open-source automation tools to meet business needs.
• Collaborate with Development, QA, and DevOps teams to integrate automation into CI/CD pipelines.
• Drive AI/ML-based solutions to enhance testing efficiency (e.g., intelligent test generation, self-healing automation, predictive defect detection).
• Define QA automation standards and governance to ensure consistency across projects.
• Mentor and guide QA engineers in advanced automation practices and solution design.
• Act as a trusted advisor to stakeholders on QA strategy, tooling, and innovation.

Required Skills & Experience

• 8+ years of hands-on experience in test automation across UI and API layers.
• Strong knowledge of multiple automation tools (e.g., Selenium, Playwright, Cypress, REST Assured, Tosca, UFT, TestComplete, etc.).
• Proven expertise in developing automation frameworks and applying design patterns (POM, Singleton, Factory, etc.).
• Proficiency in at least one programming language: Java, Node.js, Python, or C#.
• Strong understanding of CI/CD pipelines and integration with automation (Jenkins, Azure DevOps, GitHub Actions, GitLab).
• Experience in cloud ecosystems (Azure, AWS, GCP) for automation integration.
• Exposure to AI-based automation approaches (self-healing, NLP-driven test generation, etc.) is a significant advantage.
• Excellent communication and technical leadership skills with the ability to influence QA strategy across teams.

Added Advantage (not mandatory but highly valued).

• Experience with Front-End and Back-End development
• Hands-on with performance testing tools (e.g., JMeter, LoadRunner, Gatling).
• Familiarity with test data management and service virtualization.
• Exposure to containerization and orchestration (Docker, Kubernetes).
• Knowledge of DevOps and shift-left testing practices.