QA Engineer

Tavily • Israel • 1d ago

Why This Job is Featured on The SaaS Jobs

Quality engineering is increasingly central in SaaS products that expose APIs and operate distributed backends, and this QA Engineer role sits directly in that intersection. Tavily’s focus on an API that supports AI agents and RAG-style workflows points to a modern SaaS surface area where reliability depends on more than UI checks, spanning services, pipelines, and external dependencies. The added wrinkle here is validating AI-influenced behavior, where correctness can be probabilistic rather than deterministic.

For a SaaS career path, the work maps closely to how high-usage platforms mature their engineering practices: automation-first testing, CI/CD quality gates, performance validation, and production incident learning loops. Experience defining quality metrics across microservices and data flows tends to transfer well across SaaS companies, especially those building developer-facing products where regressions quickly impact customers and integrations.

This role is best suited to someone who prefers systems-level thinking and enjoys partnering with engineers to shape how software is shipped, not only how it is verified. It will likely fit a QA professional who wants deeper ownership of test strategy and tooling, and who is comfortable working on-site while tackling ambiguous evaluation problems common in AI-enabled SaaS.

The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.

Job Description

Location

Israel

Employment Type

Full time

Location Type

On-site

Department

Engineering

About Tavily

We're building the search engine for AI agents. Our API is designed from the ground up to power RAG and real-time reasoning in AI systems. By connecting LLMs to high quality, trustworthy web content, we help developers build agents that are not only intelligent, but also informed.

We work with some of the most innovative teams in AI, from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.

The Role

We're looking for a QA Engineer to own quality across our AI-powered search infrastructure. You'll work closely with engineering to ensure our APIs, scraping pipelines, and AI-driven features meet the highest standards. This role goes beyond traditional QA—you'll be testing non-deterministic AI outputs, building automation frameworks, and helping define quality metrics for LLM-integrated systems.

What You'll Do

- Design and execute test strategies for our search API, content extraction, and AI-powered research features

- Build and maintain automated testing frameworks for APIs, microservices, and data pipelines

- Develop testing approaches for non-deterministic AI outputs (LLM responses, search relevance, content quality)

- Create performance and load testing suites to ensure our systems scale reliably

- Collaborate with developers to implement CI/CD quality gates and shift-left testing practices

- Investigate production issues, perform root cause analysis, and define preventive measures

- Define and track quality metrics across our distributed system

What We're Looking For

- 3+ years of experience in QA Engineering, with strong emphasis on backend/API testing

- Hands-on experience with test automation frameworks (pytest, Playwright, or similar)

- Experience testing distributed systems, microservices, or data pipelines