Director of Quality Assurance

About Walker Digital Table Systems (WDTS)

Walker Digital Table Systems (WDTS) is the global leader in smart table gaming technology. Our patented PJM3.0TM RFID platform, combined with real-time software, analytics, and AI-driven capabilities, transforms live casino table games into secure, data-rich environments.

Our products — Perfect PayTM, Perfect TableTM, and Perfect CageTM — are deployed in high‐volume, regulated casino environments worldwide. These systems operate in mission‐critical conditions where accuracy, reliability, and release confidence are non‐negotiable.

Role Purpose

The Director of Quality Engineering is a senior technology leader accountable for product quality, release confidence, and quality‐related risk across the WDTS platform.

This role exists to address systemic quality challenges and scale quality through platform evolution and AI‐driven automation, not to manage test execution alone. The Director defines and leads a modern Quality Engineering operating model that:

- scales with architectural change, - supports complex release types (major releases, feature sets, patches, hotfixes), and - treats quality as a business and operational risk, not merely a testing activity.

A core mandate of this role is to transform Quality Engineering into an AI‐first discipline, where intelligent agents generate the majority of automated test cases, and QE leadership focuses on risk modeling, test intent, governance, and release decisioning.

The Director partners closely with Architecture, Engineering, Product, DevOps, PMO, and Support to ensure quality readiness is designed in, measured consistently, and clearly communicated at release decision points.

Key Responsibilities

1. Quality Strategy, Operating Model & Governance

- Define and own the Quality Engineering operating model across all release types, ensuring it scales with architectural change and platform evolution. - Establish a shared, defensible definition of quality readiness, incorporating change impact, regression risk, defect exposure, environment readiness, and architectural dependencies. - Shift quality from reactive testing to a risk‐based, preventative discipline, treating quality as a business and operational risk. - What success looks like: - Quality decisions are predictable, risk‐informed, and consistently understood across the organization.

2. AI‐First Quality Engineering Transformation

- Lead the transformation of QE into an AI‐first discipline, with agent‐driven test generation producing the majority of new automated coverage. - Define where AI is trusted end‐to‐end versus where human oversight and explicit quality gates remain required. - Establish governance standards for AI‐generated tests, including framework conformity, correctness, coverage, stability, and maintainability. - Champion agentic testing workflows (planning, generation, execution, healing) as a first‐class QE capability. - What success looks like: - QE effort shifts from test execution to test intent, risk analysis, and quality governance, while automation scales sustainably.

3. Test Architecture, DevOps & Continuous Quality

- Define and oversee end‐to‐end test strategies spanning embedded RFID hardware, firmware, real‐time backend systems, data integrity, UI/UX, and cross‐system integrations. - Ensure test architecture is stable, scalable, and agent‐friendly, with automation treated as a platform capability rather than a coverage metric. - Embed quality into CI/CD pipelines, defining release‐readiness standards, quality KPIs, and regression frameworks. - Own production quality feedback loops, including observability, post‐release metrics, incident RCA, and continuous improvement.

4. Release Readiness, Compliance & Executive Leadership

- Act as the single accountable leader for quality readiness at release time, ensuring decisions are driven by risk and impact rather than test counts. - Identify and escalate quality risks early, clearly articulating business, customer, and operational impact. - Partner with Compliance and Regulatory teams to ensure readiness for gaming lab certifications and regional regulatory requirements, with full traceability from requirements to validation. - Lead and develop the Quality Engineering organization as a strategic partner, representing quality and release risk credibly at senior leadership and executive forums.

What This Role Is Not:

- Not a manual testing manager role - Not a tooling‐only automation lead - Not a role measured by test counts alone

This role is accountable for:

- quality outcomes, - AI‐first QE transformation, - automation as an engineering system, - and release confidence.

Ideal Candidate Profile

Required Experience

- 10+ years in Quality Engineering, with 5+ years in senior leadership roles. - Proven experience leading quality in complex, distributed, high‐reliability systems. - Strong understanding of: - release management and regression strategy - automation frameworks and CI/CD integration - architecture‐driven quality risk - Experience operating credibly with architects, senior engineers, and executives.

Strongly Preferred

- Experience operationalizing AI‐assisted or agent‐driven test generation beyond experimentation. - Experience defining governance and evaluation frameworks for AI outputs. - Background in regulated or high‐stakes environments (gaming, fintech, medical, aerospace, defense). - Familiarity with embedded systems, real‐time transaction platforms, or hybrid edge environments.

Why This Role Exists

WDTS is evolving its platform architecture while supporting complex, regulated deployments worldwide. This role ensures that quality scales with that change, leveraging AI to improve coverage and speed without increasing risk, and that release decisions are made with clarity, consistency, and executive confidence.