Product QA & Data Engineer

About the company

FieldAI develops physics-integrated Field Foundation Models—general-purpose embodied AI that provides robots (humanoids, quadrupeds, autonomous vehicles) with risk-aware perception and decision-making for construction, energy, and urban delivery.

About this role

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. We are seeking a highly detailed and technically proficient Product QA & Data Engineer to drive quality assurance and manage data delivery for our construction intelligence platform. In this dual-function role, you will be instrumental in ensuring the reliability of our software releases and the accuracy of the spatial data products delivered to our customers. Operating as the definitive quality checkpoint, you will establish rigorous testing protocols for our application while taking ownership of the final data outputs. This role requires a blend of rigorous manual testing, the development of automated testing workflows, and the meticulous verification of complex 3D scan and BIM data. What You Will Do: Own quality assurance for all software releases, serving as the final gate to ensure robust performance and mitigate regressions prior to deployment. Conduct comprehensive manual testing and engineer automated testing frameworks to consistently validate complex UI workflows and software functionality. Identify, meticulously document, and triage software defects in issue-tracking systems (e.g., Jira), providing engineering teams with reproducible test cases and precise context. Develop lightweight scripts and automation tools to streamline testing pipelines, optimize QA workflows, and enhance release consistency. Establish and enforce rigorous standards for software reliability, performance, and user experience. Own the end-to-end data quality and delivery process, ensuring all platform outputs meet strict accuracy and formatting standards before customer handoff. Inspect, validate, and verify the integrity of 3D spatial data, point cloud processing, and architectural model comparisons within the platform. Collaborate closely with engineering and data teams to resolve data-related anomalies, debug processing errors, and continuously improve data delivery pipelines. What You Bring: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline, with 2+ years of professional experience in software QA, test engineering, or data validation. Demonstrated experience testing, troubleshooting, and validating complex software systems or data processing pipelines. Hands-on proficiency with UI/UX automation and testing tools (e.g., TestComplete, Selenium, PostHog). Exceptional organizational skills with a highly systematic approach to defect tracking, root-cause analysis, and technical documentation. A strong sense of accountability and the professional confidence to uphold quality standards, including delaying software releases or data deliveries if criteria are unmet. Excellent analytical and communication skills to effectively bridge the gap between technical teams and product requirements. What Sets You Apart: Industry experience or domain knowledge in construction technology, civil engineering, surveying, or industrial mapping. Working knowledge of 3D point cloud data, spatial data formats, and Building Information Modeling (BIM). Familiarity with foundational software development languages (e.g., JavaScript, HTML, CSS) to facilitate deeper technical troubleshooting and defect localization. Applied scripting capabilities (e.g., Python, Bash) utilized to automate backend testing, data processing, or deployment workflows. A proven track record of successfully integrating automated testing suites into CI/CD pipelines.