Senior QA AI Products (Python)

Sberhealth; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

SberHealth is seeking a Senior QA Engineer to test AI-driven health solutions, focusing on mobile and backend/API scenarios. Candidates with strong Python skills and experience in testing AI components are encouraged to apply.

The role involves testing ML components, building infrastructure for testing, and maintaining automated tests to ensure quality and reliability across health solutions. Collaboration with Product, Backend, ML, and Mobile teams is essential.

Qualifications

• Experience testing ML/AI components and validating AI outputs.
• Strong Python skills and test automation experience.
• Experience testing mobile apps and backend/API services.
• Ability to document defects and collaborate with cross-functional teams.

Responsibilities

• Test mobile and backend/API scenarios for AI-driven health solutions.
• Build infrastructure for testing ML components and maintain automated tests.
• Collaborate with Product, Backend, ML and Mobile teams to ensure release readiness.
• Document AI defects and validate scenarios where outputs may vary.

Skills

Python

QA testing

Mobile testing

API testing

AI testing

Test automation

Job description

SberHealth seeks a Senior QA Engineer to test AI-driven health solutions, focusing on mobile and backend/API scenarios. Ideal for candidates with strong Python skills and experience in testing AI components.

In this role, you will be responsible for testing mobile and backend/API scenarios for SberHealth's AI products. Your work will involve building infrastructure for testing ML components and maintaining existing automated tests, ensuring the quality and reliability of health solutions.

Collaboration with cross-functional teams, including Product, Backend, ML, and Mobile, is essential for making informed decisions about release readiness. Your expertise in testing will help document AI defects and validate scenarios where outputs may vary, contributing to a robust QA process.