SDET Python

Overview

We are seeking a highly skilled SDET with strong expertise in Python, AWS, and modern testing tools to support the development of a robust AI/ML data platform. This role focuses on building intelligent validation frameworks and infrastructure to ensure the reliability and performance of large-scale distributed systems.

• Design and develop high-performance tools and services to validate ML data pipelines and AI infrastructure.
• Build platform-level test automation frameworks using Python, Terraform, and cloud-native practices.
• Integrate automated testing, resilience checks, and observability into CI/CD pipelines.
• Lead initiatives to embed testability and validation as code across the ML platform stack.
• Collaborate with engineering, MLOps, and infrastructure teams to ensure quality across platform components.
• Develop reusable components to support scalable and modular quality tooling.
• Mentor junior engineers and contribute to technical standards within the Test Engineering Program.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 8+ years of hands-on software development experience, including backend systems or platform engineering.
• Expert-level proficiency in Python and experience with testing frameworks such as Pytest and Playwright.
• Strong experience with AWS services including Lambda, S3, ECS/EKS, Step Functions, and Cloud Watch.
• Proficiency in Infrastructure as Code using Terraform.
• Experience with CI/CD tools such as Git Hub Actions, Jenkins, or similar.
• Solid understanding of software engineering best practices including code quality, performance optimization, and observability.

• Experience in test engineering for AI/ML platforms or data infrastructure.
• Familiarity with MLOps practices and tools.