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
Quality at Gather AI spans three genuinely distinct surfaces: drones flying in warehouses, camera-based MHE Vision systems installed on forklifts and at dock doors, and a customer-facing cloud platform that ingests it all and turns it into inventory intelligence. Our QA team — currently anchored by a QA Manager and engineering team primarily based in India — has been doing strong work. But as our product lines scale and our engineering org accelerates with AI tooling, we need a Director who can raise the entire function to match.
About the Role
Most QA Director roles hand you a legacy function and ask you to keep the lights on. This one hands you a genuine mandate: build the QA strategy for an AI-first robotics company from the ground up — across hardware, ML models, and cloud software simultaneously.
As our Director of Quality Assurance, you will own the full QA surface: automated test infrastructure for drone flight and docking systems, perception model regression and evaluation, and cloud/API/UI regression for the customer platform. You’ll lead a distributed US and India team, establish release qualification gates that span hardware-to-cloud, and build an AI-assisted QA pipeline that scales throughput as the engineering org’s velocity grows. This is a role with executive visibility, real authority, and the rare opportunity to define what “quality” means at a company where the product is this technically diverse.
What You’ll Do
- Own and evolve QA strategy across all three product surfaces — drone hardware and flight systems, MHE Vision perception, and the cloud/fullstack customer platform — including release qualification gates that span the full stack
- Build automated test infrastructure from a low baseline: CI/CD test gates, API and UI regression, data pipeline validation, hardware-in-the-loop, and simulation for physical systems
- Stand up an AI-assisted QA pipeline — LLM-driven test generation, automated failure triage, model output grading, and AI-driven exploratory testing — to scale QA throughput alongside an AI-accelerated engineering org
- Lead, mentor, and level up the distributed QA team across the US and India, including directly developing the existing QA Manager and growing the team with a deliberate mix of automation engineers and high-judgment manual testers
What You’ll Need
- 10+ years in QA or test engineering with production systems at scale, including 5+ years leading QA, SDET, or test engineering teams
- Demonstrated breadth across at least two of: hardware/embedded systems QA, ML/computer vision model evaluation, and cloud/fullstack/SaaS platform QA — single-domain specialists will not have the range this role requires
- Proven track record of replacing manual test cycles with automation, instrumentation, or AI grading — and a clear philosophy for where manual QA remains irreplaceable
- Experience managing a geographically distributed team (US + India or equivalent), with the mentorship instincts and cultural fluency that requires
- Hands-on technical depth: Python, CI/CD (GitHub Actions, Jenkins, or equivalent), pytest or equivalent test frameworks, Docker, AWS or GCP, and familiarity with at least one of hardware-in-the-loop, robotics simulation, or ML model evaluation harnesses
Nice to Have
- Hardware QA or field reliability experience with sensors, cameras, embedded devices, drones, or robotics
- Experience with simulation-based testing (Gazebo, Isaac Sim, or in-house sim) for robotics or perception systems
- Background in warehouse, logistics, or industrial deployment environments
- Experience building or operating QA for a multi-tenant SaaS platform at scale
