Associate Director _ QA

Team Overview

The position in discussion is with the Tax Technology (ES) team consists of highly skilled resources that are dedicated to supporting our member firms, learning and deploying leading practices and innovative solutions, and helping our clients grow.

Our team comprises software engineers, technical leads, architects, Business Analysts, PMs, testers, test architect, data scientists, data engineers etc. with strong technical and tax domain knowledge. Team builds data/engineering products and solutions for our tax business and clients. Client engagements are run leveraging these products & solutions

The Role

The QA Principal Engineer is a senior technical and leadership role responsible for defining, driving, and governing quality engineering practices across multiple programs and teams. This role leads enterprise‑grade testing strategy, automation, and quality transformation while leveraging AI‑assisted testing, analytics, and intelligent automation to improve speed, coverage, and quality of delivery.

This role ensures that the quality of our software is maintained at the highest possible levels, increasing the satisfaction of customers and reducing the number of issues using automated technologies. The role partners closely with engineering, architecture, security, data privacy, and DevOps teams to ensure high‑quality, secure, and scalable software products.

You will have …

Proven Track Record: A proven experience vision casting, leading and mentoring others.

Review functional and design specifications to ensure full understanding of individual deliverables

Quality Strategy & Leadership

Define and drive the overall quality engineering vision, roadmap, and operating model across the organization.

Champion Agile and DevOps quality practices with a strong focus on continuous improvement.

Introduce and scale AI‑assisted quality engineering practices to enhance test coverage, efficiency, and risk detection.

Provide technical thought leadership and mentoring to QA engineers and cross‑functional teams.

Collaboration & Stakeholder Engagement, Partner with product, development, and platform teams to embed quality and intelligence early in the software lifecycle.

Communicate quality risks, AI limitations, and testing insights clearly to senior stakeholders.

Test Strategy, Planning & Governance

Review functional, non‑functional, and technical design specifications to ensure complete understanding of deliverables.

Define and maintain test strategies, standards, and governance frameworks.

Maintain a centralized, managed view of test execution, coverage, risks, and dependencies across all teams.

Ensure testing practices adhere to organizational, regulatory, and compliance standards.

Automation, AI & DevOps Enablement

Design, implement, and continuously improve scalable automation frameworks incorporating:

UI, API, and integration testing

AI‑assisted test case generation and optimization

Integrate intelligent test automation into CI/CD pipelines.

Leverage AI techniques for:

Test prioritization and selection, Defect pattern analysis

Predictive quality and risk identification

Drive shift‑left and shift‑right testing practices using modern tooling and AI insights.

API, Integration & Modern Architecture Testing

Lead and execute API and service‑level test automation for distributed, microservices‑based systems.

Ensure validation of service contracts, integrations, and data flows.

Promote best practices for testing cloud‑native and event‑driven architectures.

People Development

Actively mentor and develop QA and engineering team members.

Upskill teams in automation, modern testing practices, and AI‑assisted QA approaches.

Foster a culture of quality ownership, innovation, and continuous learning.

You may have …

Strong passion for delivering high‑quality, user‑centric software , with deep focus on user experience, accessibility, and fidelity to visual and functional design.

Proven expertise in architecting, designing, and evolving scalable test automation frameworks using Selenium or similar tools, with an enterprise mindset.

Strong hands‑on experience in C#, or similar object‑oriented programming languages , enabling code reviews, framework optimization, and technical guidance.

Demonstrated experience implementing and influencing BDD/TDD practices , partnering closely with developers to embed quality early in the development lifecycle.

Deep experience in designing and enabling CI/CD test automation pipelines , ensuring automated quality gates across build, deploy, and release workflows.

Experience leveraging AI‑assisted testing capabilities to improve test coverage, efficiency, and speed (for example: intelligent test generation, test optimization, and defect pattern analysis).

Ability to evaluate and responsibly adopt AI‑enabled QA tools to enhance manual and automated testing practices.

Understanding of quality considerations for AI‑driven features , including validation of system behavior, reliability, and unintended outcomes.

Strong capability in identifying quality risks , driving proactive mitigation strategies, and communicating risks effectively to engineering and business stakeholders.

Ability to define clear, concise, and robust test strategies and test plans aligned to business goals, architecture, and delivery models.

Expertise in applying multiple testing techniques and approaches (functional, non‑functional, risk‑based, exploratory, automation‑first) based on product and business needs.

Proven experience leading through technical influence , mentoring and guiding Manual and Automation QA Engineers across teams.

Demonstrated success in driving transformation from manual testing to automation‑ and AI‑assisted quality engineering .

Strong experience using test management and defect tracking tools such as Zephyr and Jira to provide transparency, metrics, and traceability.

Ability to collaborate effectively with Development teams, Product owners, architects, and business experts to shape quality outcomes.

Excellent verbal and written communication skills , with the ability to articulate quality risks, automation strategy, and AI‑related considerations clearly