AI Test Lead

Argyllinfotech; Georgia; Hybrid; USD 150,000 - 190,000; Full time

Job summary

Argyllinfotech in Atlanta, GA is seeking an AI Test Lead to own the quality strategy for AI-powered applications and models. You will define end-to-end AI testing, lead test execution with modern AI tools, and set the standard for trustworthy AI delivery.

The role requires 8+ years in software QA/testing with 2+ years hands-on testing AI/ML applications, experience leading QA teams, and familiarity with AI-based testing tools and CI/CD pipelines.

Qualifications

• 8+ years in software QA/testing with 2+ years hands-on testing AI/ML applications and models.
• Hands-on with AI-based testing tools and test automation.
• Ability to create and drive AI testing strategy from the ground up.

Responsibilities

• Define and own the AI testing strategy for applications and models.
• Lead AI application testing across functional, integration, and user-facing behavior.
• Perform model testing and validation (accuracy, robustness, bias, drift, hallucination, and performance).
• Leverage AI-powered testing tools to design, automate, and accelerate test coverage.
• Establish test frameworks, quality gates, and acceptance criteria for AI features.
• Collaborate with data science, engineering, and product teams to embed quality early.
• Report on quality metrics, risks, and readiness for release.

Skills

AI testing strategy

QA leadership

Test automation

Model evaluation metrics

AI/ML risk & bias

Tools

AI testing tools

CI/CD pipelines

Job description

AI Test Lead
Atlanta, GA - Hybrid

Exp: 12+ years

About the Role

We are looking for an AI Test Lead with 8+ years of overall testing experience, including 2+ years testing AI/ML systems, to own the quality strategy for our AI-powered applications and models. You will define how we test AI systems end-to-end, lead testing execution using modern AI tools, and set the standard for reliable, trustworthy AI delivery.

Key Responsibilities

• Define and own the AI testing strategy for applications and models.
• Lead AI application testing across functional, integration, and user-facing behavior.
• Perform model testing and validation (accuracy, robustness, bias, drift, hallucination, and performance).
• Leverage AI-powered testing tools to design, automate, and accelerate test coverage.
• Establish test frameworks, quality gates, and acceptance criteria for AI features.
• Collaborate with data science, engineering, and product teams to embed quality early.
• Report on quality metrics, risks, and readiness for release.

Required Skills & Experience

• 8+ years in software QA/testing, with 2+ years hands-on testing AI/ML applications and models.
• Hands-on with AI-based testing tools and test automation.
• Ability to create and drive AI testing strategy from the ground up.
• Strong understanding of model evaluation metrics and AI failure modes.
• Proven experience leading QA teams and mentoring testers.

Nice to Have

• Experience testing LLM / GenAI applications (prompt testing, RAG evaluation).
• Familiarity with CI/CD and MLOps pipelines.