Director of AI-Driven Quality Engineering

twentysix; New York (NY); Hybrid; USD 58,000 - 115,000; Full time

Job summary

Huge is looking for a Director, Quality Engineering to lead our globally distributed QA practice from Bogota, Colombia. You will shape a 75+ QA team across four countries and drive the shift from manual testing to AI-augmented quality engineering across the full software lifecycle.

Define AI-native quality frameworks, governance, and tooling standards. Partner with engineering, product, and design to embed quality across design, development, and release.

Qualifications

• Define and implement an AI-native quality engineering strategy across four global offices.
• Lead the shift from manual to AI-augmented automated testing at scale.
• Embed quality across the full SDLC with AI-powered gates and shift-left practices.
• Design governance frameworks and quality health metrics.
• Lead and develop a globally distributed team of 75+ QA engineers and professionals.

Responsibilities

• Define and advance an AI-native quality engineering strategy that treats quality as a continuous discipline across four global offices.
• Lead the shift from manual to AI-augmented automated testing across web, mobile, and API platforms.
• Embed quality across the full SDLC by partnering with engineering, product, design, and BA leadership.
• Design and socialize automation maturity models and governance frameworks for consistency across teams.
• Lead, coach, and develop a globally distributed QA team of 75+ across QA Leads and Managers.
• Serve as a credible quality engineering voice in client conversations with business development and delivery teams.

Skills

Global QA leadership

AI-native QA

Automation tooling

CI/CD integration

Cross-country management

Executive communication

Tools

Playwright

Cypress

Appium

Testim

Mabl

Applitools

Job description

Huge is looking for a Director, Quality Engineering to lead our globally distributed QA practice from Bogota, Colombia. You will shape a 75+ QA team across four countries and drive the shift from manual testing to AI-augmented quality engineering across the full software lifecycle.

Define AI-native quality frameworks, governance, and tooling standards. Partner with engineering, product, and design to embed quality across design, development, and release.