Senior QA Engineering

Join us in building the systems that turn complex data into better business decisions across the food supply chain, while helping tackle climate change. About Us: Nibbana connects what happens on farms with the decisions made across global food and agriculture supply chains. We bring together farm-level information, complex supply-chain datasets, and data from large multinational companies to create value for farmers, cooperatives, and food businesses. Our approach combines software, data infrastructure, and AI/ML with deep agricultural expertise and hands-on implementation. We turn complex data into actionable insights for farmers and food companies, help producers implement practical changes, and connect verified outcomes to transparent reporting and financial incentives. We’re an early-stage, well-funded climate-tech startup working with industry leaders. We’re building our core platform from the ground up and looking for engineers who want meaningful ownership over product quality and the systems our customers rely on. The Role: We’re looking for a QA Engineer who tests data as rigorously as features - and keeps digging until they can explain exactly what went wrong. You’ll combine exploratory testing with automation across our applications, APIs, and data pipelines. You’ll develop a deep understanding of how the system works, how data moves through it, and how business rules shape the results our customers see. What You’ll Do: Own testing across product features, integrations, and data workflows. Investigate issues beyond the symptoms, tracing behavior and data to understand the underlying cause. Build automated tests and data checks that catch regressions and strengthen release confidence. What We’re Looking For: +5 year of hands-on QA experience with production applications and data-intensive systems. Strong SQL skills and confidence working directly with raw data. Experience testing APIs and building automation with TypeScript, JavaScript, or Python. Nice to Have: Experience with data pipelines, enterprise integrations, or mobile testing. Familiarity with CI/CD, event-driven systems, or AI/ML validation. Experience establishing QA practices in a startup. Shape product quality and testing practices from the ground up. Work on complex systems where data accuracy has real business and environmental impact. Join a small team with meaningful ownership, direct collaboration, and a modern, AI-native engineering culture.