Director of Quality

Gather AI•Pittsburgh, PA

7d•Onsite

About The Position

Gather AI is seeking a Director of Quality Assurance to build the QA strategy for an AI-first robotics company from the ground up, covering hardware, ML models, and cloud software. This role involves owning the full QA surface, including automated test infrastructure for drone flight and docking systems, perception model regression and evaluation, and cloud/API/UI regression for the customer platform. The Director will lead a distributed US and India team, establish release qualification gates, and build an AI-assisted QA pipeline to scale throughput. This position offers executive visibility and the opportunity to define quality standards for a technically diverse product in the rapidly evolving robotics industry and global supply chain. Quality at Gather AI encompasses drones, MHE Vision systems, and a customer-facing cloud platform. The current QA team, led by a QA Manager and an engineering team in India, requires a Director to elevate the function as product lines scale and engineering accelerates with AI tooling.

Requirements

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
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
Pittsburgh-based or genuinely willing to relocate

Nice To Haves

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

Responsibilities

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
Establish ML/perception model evaluation methodology and release qualification criteria, working directly with ML and autonomy leads to qualify model upgrades for production
Partner cross-functionally with engineering, autonomy, cloud, and field ops to align QA with deployment realities and customer-reported quality issues