Lead, Quality Engineering and Testing

POSITION SUMMARY: 

POSITION SUMMARY:

The full-stack Lead Developer reports to the Sr. Manager of Software Engineering and brings substantial experience in software engineering principles and best practices, solution design, design patterns, the latest technologies, technical troubleshooting techniques, application testing, and DevOps. This role requires in-depth expertise in NextJS, React, Java, NodeJS and relevant database technologies, crucial for one or more business applications. The full-stack Lead Developer must demonstrate strong interpersonal and collaboration skills and is responsible for leading the team in executing product deliverables, implementing complex engineering solutions, and ensuring operational excellence for software systems and applications within the product portfolio.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

End-to-End Solution Implementation: Lead the design and implementation of solutions from inception through delivery to production.

Team Leadership: Lead and mentor a team of engineers and a team of QA automation engineers, fostering a culture of innovation, accountability, and continuous improvement.

QA Automation Strategy: Guide QA engineers in expanding and maintaining our evolving QA automation platform, increasing test coverage, reliability, and speed of delivery across applications.

AI Adoption: Drive adoption of AI-assisted tools and practices across engineering and QA, including AI-supported coding, code review, test generation, and test maintenance. Coach teams on effective and responsible use, and measure the impact on quality and productivity.

Operational Excellence: Design and code for resiliency, performance, availability, and scalability of applications.

Estimation and Planning: Provide accurate estimates in collaboration with product teams and ensure compliance with corporate standards and policies.

Documentation: Document solution designs and engineering decisions for product and application solutions.

Industry Awareness: Stay current with industry and AI trends to advise on and advocate solution approaches that meet evolving business needs.

Additional Responsibilities: Perform other job-related duties as assigned by the supervisor or management.

QUALIFICATIONS

Educational Background: Bachelor or Master of Science in Engineering, Computer Science, Information Technology, Math, or a related field.

Experience: 7+ years of experience in Software Engineering, with a strong background in both frontend and backend development.

Team Experience: Preferably experienced in working with large, cross-functional teams in a globally diverse model.

KNOWLEDGE AND SKILLS

Possesses extensive proficiency, experience, and understanding of the core competencies outlined below.

Software Engineering

Development Expertise: Strong understanding of algorithms and technologies, with the ability to design, write, test, and debug applications using Next.js, React, Java, and relevant databases.

Lifecycle Knowledge: Awareness of various lifecycle models, optimization tools, and design patterns, including how AI tooling fits into each phase of the software development lifecycle.

Code Quality: Key contributor to writing code and unit tests, capable of performing code reviews and ensuring code quality and security, including review of AI-generated code.

AI-Assisted Development

AI Tooling Proficiency: Hands-on experience with AI coding assistants and agentic tools (such as GitHub Copilot, Claude Code, or Cursor) and the judgment to know when and how to apply them effectively.

Responsible AI Use: Understanding of data classification, security, and compliance considerations when using AI tools, and the ability to establish team guidelines and guardrails.

Enablement: Ability to coach engineers and QA staff on practical AI workflows, and to measure and communicate the impact on quality and productivity.

Software Solutioning

Solution Evaluation: Evaluate software solutions and best practices for product implementation.

Design and Implementation: Resolve issues in software solution components and ensure they align with enterprise-wide architecture.

Software Product Technical Knowledge

Architecture and Integration: Deep knowledge of software architecture, configurations, integration, and implementation options.

Documentation and Deployment: Document technical components and deploy them to the defined infrastructure of the software product.

Technical Troubleshooting

Problem-Solving: Proactively communicate problems, perform advanced diagnostics, and understand the business impact of technical issues.

Issue Resolution: Effectively troubleshoot and resolve software issues, creating detailed trouble reports and proposing solutions.

Application Testing and QA Automation

Testing Strategies: Design, plan, and execute testing strategies to ensure software quality.

Test Code: Write effective unit and component-level tests, and understand integration and end-to-end regression testing.

Test Automation Frameworks: Experience designing, scaling, and maintaining automated test platforms and frameworks (for example, Playwright, Cypress, Selenium, or similar), including integration into CI/CD pipelines.

AI in Testing: Familiarity with applying AI to test generation, test maintenance, and failure analysis, and the ability to guide QA engineers in adopting these practices.

EXPERIENCE AND SKILLS

Subject Matter Expertise: Extensive experience with NextJS, React, Java, and database technologies.

Domain Knowledge: In-depth understanding of software product domains.

Technology Expertise: Proven track record of leading teams and delivering high-quality, scalable software solutions.