AI SDET
Core
Design and execute test strategies for AI-driven systems, including LLM-powered features, machine learning components, and intelligent automation workflows.
Role type
Senior AI SDET (Software Development Engineer in Test)
Builds
Validated AI/ML features, reliable data pipelines, and high-quality AI experiences for customers.
Domain
Artificial Intelligence / Machine Learning / Data Infrastructure
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Python, AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face, Azure AI, AWS AI/ML, Google Vertex AI), MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI), Linux/UNIX, Docker, storage technologies (block, object, NFS, distributed file systems), QA methodologies, SDLC, agile practices
Preferred skills
Model inference behavior evaluation, prompt/response quality assessment, drift/bias/fairness analysis, LLM-based system testing
Technologies
Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, Azure AI, AWS AI/ML, Google Vertex AI, MLflow, Kubeflow, SageMaker, Vertex AI, Docker, S3, NFS
Responsibilities
Test and validate AI/ML features across internal models and integrated services; Assess model inference quality, prompt/response behavior, performance, safety, and robustness; Validate data contracts, feature schemas, and payload structures; Ensure AI-driven workflows function reliably across components and applications; Build tools to simulate AI behavior, automate evaluation workflows, and generate test datasets; Identify edge cases, failure modes, drift indicators, and quality gaps; Validate compliance with security, privacy, fairness, and responsible AI guidelines; Collaborate with product, engineering, and data science teams to troubleshoot issues and improve readiness; Produce documentation for AI test plans and validation procedures.
Seniority
Senior, hands-on IC