Head of Quality Assurance

As the Director/Head of Quality Assurance, you are the executive leader responsible for setting the global quality vision, automation strategy, and engineering standards for Impact Analytics' enterprise AI platforms. You will lead, scale, and mentor a high-performing global QA organization, ensuring our mission-critical Agentic AI engines, complex mathematical models, and enterprise SaaS platforms meet flawless performance, accuracy, and reliability standards across Fortune 500 deployments.

The core responsibilities for the job include the following:

QA Strategy, Vision, and Executive Leadership:

• Define and execute the multi-year global QA vision, test architecture, and quality governance for all AI SaaS product lines.
• Establish key quality KPIs (defect escape rate, automation coverage, CSAT impact) and report metrics to executive leadership.
• Lead, hire, and mentor a world-class QA engineering team across SDET, Performance, Security, and AI Testing tracks.

Test Automation and AI Engine Quality Assurance:

• Drive the shift-left quality strategy and architectural design of scalable, automated test frameworks.
• Establish rigorous validation frameworks for AI agents, machine learning models, simulation logic, and complex data pipelines.
• Integrate automated testing seamlessly into enterprise CI/CD pipelines (GitHub Actions, Jenkins) for continuous delivery.

Cross-Functional Governance and Delivery Risk Management:

• Partner closely with the VP of Engineering, VP of Product, and Success Architects to manage release quality and go-live risk.
• Institute standardized regression packs, non-functional testing (performance, load, security, and scalability), and patch validation protocols.
• Drive post-incident root-cause analysis (RCA) and implement preventive actions to continuously elevate platform stability.

Process Optimization and Knowledge Leadership:

• Transform manual QA processes into hyper-automated, continuous quality engineering workflows.
• Build and champion a company-wide quality culture, runbooks, and best-practice repositories.
• Introduce cutting-edge AI-assisted testing tools and frameworks to accelerate test generation and execution.

Requirements:

• 15-19 years of progressive experience in software quality engineering, test automation, and QA leadership within enterprise SaaS, AI/ML, or complex supply chain products.
• At least 5+ years of experience managing multiple product QA teams.
• Proven track record of building, scaling, and managing global QA organizations across automation, performance, security, and algorithmic testing.
• Deep expertise in establishing modern test automation frameworks (Python, Selenium, Playwright, Cypress, REST Assured, CI/CD pipelines).
• Hands-on background in testing data-heavy, algorithmic, or AI/ML-driven planning engines (validating model precision, simulation logic, data pipelines, and SQL/MDX).
• Strategic leadership experience defining global QA roadmaps, quality metrics (defect escape rate, test coverage, and SLA adherence), and executive reporting.
• Extensive experience with enterprise SaaS deployment architectures, multi-tenant cloud platforms (AWS, Azure, GCP), and security/compliance standards.
• Demonstrated partnership with engineering, product management, and customer success leaders to embed a 'quality-first' culture across the SDLC.
• Strong executive presence and communication skills to engage directly with enterprise client CTOs, IT leaders, and business stakeholders during critical go-lives and QBRs.
• Certification in ISTQB (Advanced/Expert Level), Agile/Scrum Leadership, or AI/ML testing practices.