Lead Software Development Engineer in Test

Job Information

Core Skills

AI Testing Areas

• RAG Pipeline Validation
• Hallucination Detection
• Model Drift Testing
• Bias & Fairness Evaluation
• AI Automation Framework Design
• Performance & Scalability Testing
• MLOps Validation
• Enterprise AI Quality Strategy

Key Responsibilities

• Define enterprise-wide QA strategy for AI products.
• Architect scalable automation frameworks for AI systems.
• Design testing approaches for RAG, hallucinations, drift, and bias.
• Lead AI quality initiatives across engineering teams.
• Establish testing standards, tools, and best practices.
• Mentor QA engineers and build AI testing capabilities.

Required Skills

• 7+ years in QA, SDET, or Quality Engineering.
• Hands-on experience with AI tools and model testing.
• Expertise in reusable automation framework architecture.
• Strong leadership and cross-functional collaboration skills.
• Knowledge of RAG, hallucination, drift, and bias validation.
• Ability to define enterprise AI testing strategies.

Bonus Skills

• Experience with AWS, Azure, or Google Cloud.
• Knowledge of CI/CD pipelines and DevOps practices.
• Exposure to MLOps workflows and AI monitoring.
• Performance and scalability testing for AI applications.

Why This Role Matters

Modern AI platforms require scalable quality engineering strategies that go beyond traditional testing. This leadership role focuses on building enterprise-grade AI quality frameworks, reducing model risk, validating LLM behavior, and ensuring reliable AI experiences for millions of users worldwide.

Disclaimer: This job information is shared for career guidance purposes only. Applications are processed through the employer's official recruitment platform.