QA Engineer

FriendliAI•San Francisco, CA

24d

About The Position

Friendli Suite is our SaaS platform that includes microservices, a frontend, multi-cloud infrastructure, enterprise authentication, billing, and organization management. However, what makes this role unique is that our platform delivers AI inference. Validating whether inference works well is a problem that traditional QA methods do not fully solve. A deployment can succeed technically and still produce poor inference. We are looking for a dedicated QA engineer who can own the product's quality, ensuring our product works the way any well-run SaaS platform should, while also developing the approaches needed to validate AI inference quality, model deployments, and integrations that traditional testing alone cannot cover.

Requirements

3+ years of experience in software quality engineering, with a track record of owning test strategy.
Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent.
Proficiency in Python and hands-on experience with pytest for test automation.
Experience with load and performance testing tools such as Locust.
Experience with browser automation and end-to-end testing frameworks such as Playwright.
Working knowledge of LLM serving.
Strong experience testing distributed systems with multiple interconnected components.
Strong systems thinking.
Comfortable working in a fast-moving environment.

Nice To Haves

Familiarity with AI infrastructure or model serving systems
Experience building QA infrastructure from scratch in an early-stage or scaling environment.
Background in performance and scalability testing for cloud-native or multi-cloud systems.
Experience covering both backend and frontend testing in a single role.
Exposure to observability tooling and how it supports debugging and quality validation.

Responsibilities

Own quality across FriendliAI's full platform stack: backend microservices, frontend, model deployments, and inference pipelines.
Build and maintain automated test suites using pytest, covering unit, integration, and regression testing across backend services.
Develop and run load and scalability tests using Locust to validate platform performance under real-world conditions.
Own frontend and end-to-end testing with Playwright across the full user-facing product.
Design and implement test strategies that account for LLM inference.
Work closely with infrastructure and backend engineers to validate model deployment workflows, multi-cloud orchestration, and service integrations.
Identify coverage gaps, prioritize test investment, and build tooling and pipelines.