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19 hours ago

Applied AI Engineer (f/m/x) - MAIA [Remote] — Leipzig

Apr 14, 2026 at 08:30 PM

<p>MAIA is the AI platform built for industrial companies - where generic AI tools break down because the data is complex, the stakes are high, and precision actually matters. We focus on the hard problems: integrating with real engineering workflows, understanding complex technical documents, and turning implicit organizational knowledge into something the whole company can build on.</p> <p>Our goal is to become the leading AI knowledge management platform for industrial companies in Europe - built for the companies that shape the physical world.</p> <p>Our team consists of structured organizational talents, creative minds, and technology-enthusiastic engineers, all with several years of experience in B2B SaaS and AI.</p> <p>We are looking for an Applied AI Engineer (f/m/x) to join our engineering team - someone who ships production-grade AI features end-to-end, from retrieval pipelines and agentic workflows to the APIs that power them.</p> <h2>Tasks</h2> <ul> <li>You build and evolve MAIA's core product capabilities. Your focus is backend and AI systems - RAG pipelines, retrieval strategies, agentic workflows, and LLM integrations that work reliably in production.</li> <li>You design, implement, and ship features from discovery to production rollout, with a strong focus on backend and AI functionality.</li> <li>You build and iterate on RAG pipelines, retrieval strategies, and LLM integrations, making pragmatic tradeoffs across quality, latency, and cost.</li> <li>You build evaluation approaches for LLM features - quality gates, regression detection, and observability that makes non-deterministic systems debuggable.</li> <li>You proactively scout new technologies and approaches, translate findings into production-ready solutions, and push the team's understanding of what is possible.</li> <li>You collaborate closely with Product, DevOps, and customer-facing teams to turn requirements into high-quality, maintainable software.</li> </ul> <h2>Requirements</h2> <p>Tech

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Manifest Local
19 hours ago

<p>MAIA is the AI platform built for industrial companies - where generic AI tools break down because the data is complex, the stakes are high, and precision actually matters. We focus on the hard problems: integrating with real engineering workflows, understanding complex technical documents, and turning implicit organizational knowledge into something the whole company can build on.</p> <p>Our goal is to become the leading AI knowledge management platform for industrial companies in Europe - built for the companies that shape the physical world.</p> <p>Our team consists of structured organizational talents, creative minds, and technology-enthusiastic engineers, all with several years of experience in B2B SaaS and AI.</p> <p>We are looking for an Applied AI Engineer (f/m/x) to join our engineering team - someone who ships production-grade AI features end-to-end, from retrieval pipelines and agentic workflows to the APIs that power them.</p> <h2>Tasks</h2> <ul> <li>You build and evolve MAIA's core product capabilities. Your focus is backend and AI systems - RAG pipelines, retrieval strategies, agentic workflows, and LLM integrations that work reliably in production.</li> <li>You design, implement, and ship features from discovery to production rollout, with a strong focus on backend and AI functionality.</li> <li>You build and iterate on RAG pipelines, retrieval strategies, and LLM integrations, making pragmatic tradeoffs across quality, latency, and cost.</li> <li>You build evaluation approaches for LLM features - quality gates, regression detection, and observability that makes non-deterministic systems debuggable.</li> <li>You proactively scout new technologies and approaches, translate findings into production-ready solutions, and push the team's understanding of what is possible.</li> <li>You collaborate closely with Product, DevOps, and customer-facing teams to turn requirements into high-quality, maintainable software.</li> </ul> <h2>Requirements</h2> <p>Tech

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