Product Engineer (Backend/AI) @Briink

What we do At Briink , we’re building AI technology for the global sustainability economy. We work with the world’s largest climate organizations, including CDP and PRI, and multinational companies such as Bayer, Siemens, Commerzbank, E.ON, and Heidelberg Materials. Our technology helps automate how sustainability data is collected, analyzed, verified, and acted on. Through our work with global climate organizations, what you build at Briink will directly impact the sustainability workflows of more than 30,000 companies, investors, and cities worldwide. We’re a small team working at enormous scale. Your code won’t sit behind an internal tool or an experimental demo — it will help shape how some of the world’s largest organizations understand and act on their environmental impact. Based at Berlin’s AI Campus, with a second office in London, and backed by over €7 million in funding, we want to prove that some of the world’s most powerful technology can also be a powerful force for good. Application requirement: Intro video As part of your application, please submit a short intro video (max 2 minutes) answering: Who you are and what you have done/built that is relevant for this role. Why you’re excited about owning and shipping AI-powered products at Briink. Why Briink’s sustainability mission resonates with you. Upload your video using this form (YouTube unlisted, Loom, or any other solution is fine). We do this to get a better sense of candidates before continuing the process. Any application without a video will not be considered ;) Your role As Briink’s Backend/AI Product Engineer , you’ll join a small, high-ownership product and engineering team building AI-powered products for sustainability professionals. This is not a narrowly scoped backend role. You’ll take meaningful product problems from initial discovery and user conversations through technical design, implementation, and iteration to deploy them at scale across the ESG market. You’ll combine strong backend and AI/LLM engineering with product judgement and the initiative to work out what should be built - not just how to action a predefined ticket. You will: Own product features end to end , from understanding the user problem and defining the right approach through to delivery, measurement, and improvement. Design and build scalable backend systems , including APIs, data models, workflows, and infrastructure for complex enterprise products. Build and ship applied AI/LLM features , such as LLM chains, RAG systems, tool-using agents, structured-output pipelines, and evaluation workflows Create reusable, extensible platform building blocks that support multiple user journeys and reporting workflows rather than solving each problem in isolation. Improve the robustness of our systems , strengthening reliability, testing, observability, performance, and maintainability as we scale. Work directly with users, product, and data , using qualitative feedback and product data to understand the rea