Remote AI Quality Architect & Testing Strategy Lead

TEKsystems; Austin (TX); Remote; USD 128,000 - 192,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) Retirement Plan

Life Insurance

HSA

PTO

Job summary

TEKsystems is seeking a senior Practice Architect to lead AI-driven quality engineering across client engagements. You will design test strategies for traditional and AI-enabled systems, including ML models and GenAI, and guide delivery teams in trustworthy AI adoption.

The role is senior, client-facing, responsible for SoWs, estimates, and reusable accelerators. Strong architecture background with QE fundamentals is essential. Ready to shape AI testing at scale.

Qualifications

• 10+ years in software development or quality engineering, or system integration; 3+ years in an architect role.
• Proven ability to design enterprise test strategies and automation architectures from scratch.
• Hands-on experience testing AI/ML and GenAI systems with risk considerations like drift and bias.
• Experience using open-source and commercial AI models to build testing solutions or accelerators.
• Strong knowledge of UI/API automation, CI/CD, and cloud platforms.

Responsibilities

• Architect end-to-end quality engineering solutions for enterprise apps, data platforms, and AI-enabled systems.
• Provide architectural direction, set standards, and ensure scalable, secure, maintainable solutions.
• Evaluate tools and AI models for fit, cost, risk, security, and client constraints.
• Grow CQ practice by defining best practices and reusable patterns.
• Embed AI quality gates into CI/CD and MLOps workflows; monitor production.

Skills

Architectural leadership

Quality engineering

AI/ML testing

Client-facing advisory

Education

Bachelor's degree in computer science or related field

Tools

Playwright

Selenium

Rest Assured

Karate

AWS/Azure/GCP

Job description

TEKsystems is seeking a senior Practice Architect to lead AI-driven quality engineering across client engagements. You will design test strategies for traditional and AI-enabled systems, including ML models and GenAI, and guide delivery teams in trustworthy AI adoption.

The role is senior, client-facing, responsible for SoWs, estimates, and reusable accelerators. Strong architecture background with QE fundamentals is essential. Ready to shape AI testing at scale.