Principal Software Engineer

The Principal Quality Engineer serves as the senior technical authority responsible for advancing the organization’s quality engineering practices, automation frameworks, and testing strategies. This role provides architectural leadership for complex testing solutions across multiple technologies, platforms, and client environments.

The Principal Quality Engineer designs and evolves enterprise testing frameworks, establishes testing standards and processes, and drives the adoption of modern automation, performance testing, and quality engineering practices. This role acts as a technical escalation point for complex testing challenges and collaborates closely with engineering teams, architects, and clients to diagnose complex issues, design solutions, and ensure the successful delivery of high-quality software systems.

The Principal Quality Engineer provides strategic technical leadership, mentors engineering teams, collaborates with global engineering groups, and contributes to innovation initiatives, including AI-driven Software Development Life Cycle (SDLC) approaches and engineering automation solutions.

Key Responsibilities

•         Architect and maintain scalable automation frameworks supporting UI, API, integration, data validation, performance, and end-to-end testing across multiple technology platforms.

•         Define testing strategies and quality engineering standards that ensure systems meet functional, performance, scalability, security, and reliability requirements.

·       Define enterprise quality engineering strategies including test observability, shift-left testing practices, and quality metrics that enable data-driven engineering decisions.

·       Drive continuous testing practices across CI/CD pipelines ensuring automated quality gates, test reporting, and release confidence.

•         Evaluate, select, and standardize automation tools, frameworks, and testing technologies; conduct proofs of concept and guide adoption of emerging engineering tools.

•         Drive innovation in quality engineering by exploring AI-enabled SDLC approaches, and automation accelerators that improve productivity and testing effectiveness.

•         Assess testing maturity and engineering practices across projects and client environments and implement process improvements that enhance automation adoption and software quality.

•         Serve as the technical escalation point for complex automation and testing challenges, diagnosing issues with frameworks, pipelines, and testing environments.

•         Support pre-sales and consulting activities by presenting testing strategies, defining implementation approaches, and recommending technical solutions for client engagements.

·       Support multiple projects simultaneously by prioritizing technical initiatives, providing effort estimates, and ensuring the successful delivery of engineering solutions.

Qualified candidates will meet the following expectations:

•         Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

•         12+ years of experience in software quality assurance, test automation, or quality engineering.

•         Strong experience designing and implementing scalable automated testing frameworks.

•         Proficiency in programming languages such as Java, C#, Python, or similar.

•         Experience with modern automation platforms such as Tosca, UFT One, Selenium, Playwright, Katalon, Cypress, or similar tools.

•         Experience testing APIs, web applications, enterprise platforms, and distributed systems.

•         Experience integrating testing frameworks into CI/CD pipelines and DevOps environments.

•         Strong understanding of the software development life cycle (SDLC) and modern testing methodologies.

•         Demonstrated ability to diagnose complex technical issues and translate conceptual ideas into practical engineering solutions.

•         Experience presenting technical strategies to technical and non-technical stakeholders.

•         Strong analytical, communication, and leadership skills with the ability to mentor engineering teams.

Preferred Skills

•         Experience implementing enterprise-level automation strategies across multiple technologies.

•         Experience with performance testing tools such as LoadRunner, NeoLoad, or k6.

•         Experience with test data management, data validation, and data engineering for testing.

•         Experience leading testing initiatives in enterprise or consulting environments.

•         Experience working within Agile or DevOps development environments.

•         Familiarity with applying AI and machine learning technologies to software testing and engineering workflows.