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Salary
$20k – $50k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Senior · 8+ years exp
Overview
Company
Impact
Profile match
Gather AI is a warehouse inventory monitoring company headquartered in Pittsburgh, Pennsylvania, and founded in 2019 as a spin-off from Carnegie Mellon University. The company flies autonomous drones through storage aisles to scan barcodes and pallet locations, then reconciles what it sees against the warehouse management system. It works with third party logistics providers, distributors, and manufacturers that would otherwise count inventory manually with lift trucks.

About Us

Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.

If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

You’ll work most closely with the fullstack engineering team and their leads, collaborating regularly with the cloud engineering team on API and backend testing, and with the ML team for feature validation. Cross-departmentally, you’ll work with Product Management on acceptance criteria and release readiness, and with Customer Support on field-reported issues.

About the Role

We are looking for a Senior QA Engineer to own the end-to-end test automation strategy for Gather AI’s fullstack platform. You will build and maintain Playwright-based E2E test suites, design API automation coverage, integrate tests into CI/CD pipelines, and develop a structured evaluation framework for LLM-powered features.

This is a greenfield opportunity to shape QA practices and tooling from the ground up at a production AI/robotics company - not a ticket-closing QA factory. Your work directly affects product quality for real customers.

What You’ll Do

  • Build and maintain Playwright-based E2E test automation suites covering critical user workflows, API validation, and edge case handling across web applications
  • Design and implement a comprehensive API automation framework for backend services, including REST endpoint coverage and data validation
  • Integrate automated test suites into CI/CD pipelines (GitHub Actions) with reporting, failure alerting, and quality gates
  • Develop a structured LLM tool evaluation framework - defining test methodologies, evaluation criteria, and repeatable benchmarks for AI/ML-powered features
  • Identify and address gaps in test coverage, flaky tests, and QA technical debt; drive adoption of quality metrics (test coverage, defect escape rate, automation coverage)
  • Collaborate with engineering leads, Product, and Customer Support to define release readiness criteria and prioritize regression coverage

What You’ll Need

  • 5-8+ years of QA/test engineering experience with a strong focus on automation
  • Hands-on Playwright experience building and maintaining E2E test suites (TypeScript/JavaScript)
  • API test automation expertise using tools such as Playwright API testing, Postman/Newman, or pytest
  • CI/CD integration experience (GitHub Actions, Jenkins, or similar) with test pipeline design and reporting
  • BS in Computer Science, Engineering, or a related field; solid functional testing fundamentals and strong analytical thinking

Nice to Have

  • Experience or aptitude for LLM/AI tool evaluation (prompt testing, output quality assessment, hallucination detection)
  • Performance or load testing experience (k6, Locust, JMeter, or similar)
  • Experience with database testing and data validation (SQL, data pipeline verification)
  • Familiarity with Docker or containerized test environments
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