Senior Software Engineer - Data & AI Platform (m/w/d)

<div><span style="font-size: 18px"><b>Redefine the future of live entertainment tech</b></span></div><div><br></div><div>Welcome to vivenu, the global leader in event ticketing tech and one of the world’s fastest-growing live entertainment tech firms. We are transforming event ticketing for global leaders like the Grammys, the Golden Globes, Stanford University and the Hockenheimring turning what was once a simple transaction into a strategic business advantage. Backed by over $65 million in funding, our platform empowers event organizers to own their brand experience, unlock deep data insights, and seamlessly integrate ticketing into their digital infrastructure.</div><div><br></div><div>With six offices worldwide and growing, we deliver a customizable, intuitive solution and industry-leading support that simplify even the most complex ticketing challenges –&nbsp;helping organizers deliver exceptional experiences and drive real growth.</div><div><br></div><div>Join us and build the future of live entertainment.</div><div><br></div><div> <div>With&nbsp;over <strong>10 million end users</strong>&nbsp;and usage quadrupling annually, our infrastructure now handles&nbsp;<strong>over 1 billion requests per month</strong>&nbsp;— and counting. Our API-first platform solves complex system challenges at scale — delivering performance, flexibility, and reliability for the world’s leading live entertainment brands.</div> </div><br><strong>As a Senior Software Engineer - Data & AI Platform (d/f/m) your responsibilities will include:</strong><br><div> <div> <div> <h3><span data-markdown-start-index="2464">Your Responsibilities:</span></h3> <li> <p><strong><span data-markdown-start-index="2493">Build Analytical Query Engines:</span></strong><span data-markdown-start-index="2526"><strong> </strong>Connect our transactional backends (MongoDB) with modern analytical event stores (ClickHouse) to support sub-second aggregations across millions of ticket transactions.</span></p> </li> <li> <p><strong><span data-markdown-start-index="2699">Implement AI Retrieval &amp; Reporting Workflows:</span></strong><span data-markdown-start-index="2746"> Build and deploy Retrieval-Augmented Generation (RAG) pipelines, semantic parsers, and agentic query supervisors that convert natural language prompts into deterministic, accurate SQL and aggregation queries.</span></p> </li> <li> <p><strong><span data-markdown-start-index="2959">Maintain Low-Latency Reporting APIs:</span></strong><span data-markdown-start-index="2997"> Write high-performance production services in </span><span data-markdown-start-index="3046">Go</span><span data-markdown-start-index="3050"> or </span><span data-markdown-start-index="3056">TypeScript/Node.js</span><span data-markdown-start-index="3076"> that power real-time reporting dashboards for global organizers without degrading transactional processing.</span></p> </li> <li> <p><strong><span data-markdown-start-index="3188">Centralize Data Flows &amp; Auditing:</span></strong><span data-markdown-start-index="3223"> Partner with platform and security teams to build clean data schemas, strict audit trails, and automated evaluation suites that catch hallucinated data or metric drifts before they reach clients.</span></p> </li> <li> <p><strong><span data-markdown-start-index="3423">Sprint Scoping &amp; Architecture:</span></strong><span data-markdown-start-index="3455"> Collaborate directly in monthly in-person architecture sessions in Frankfurt alongside the VP of Engineering, CTO, and engineering leads to define technical milestones.</span></p> </li> </div> </div> </div><br><strong>What you will need to succeed in this role:</strong><br><div> <div> <div> <li> <p><strong><span data-markdown-start-index="3685">5+ years of hands-on experience</span></strong><span data-markdown-start-index="3718"><strong> </strong>building high-throughput, distributed production services using </span><span data-markdown-start-index="3785">Go, Python, or TypeScript/Node.js</span><span data-markdown-start-index="3820">.</span></p> </li> <li> <p><strong><span data-markdown-start-index="3825">Analytical Warehousing Experience:</span></strong><span data-markdown-start-index="3861"><strong> </strong>Direct, hands-on production experience with </span><span data-markdown-start-index="3908">ClickHouse</span><span data-markdown-start-index="3920"> (or closely related low-latency analytical engines like DuckDB, Snowflake, or Apache Pinot) for high-volume event streams.</span></p> </li> <li> <p><strong><span data-markdown-start-index="4047">Database Mastery:</span></strong><span data-markdown-start-index="4066"> Solid practical experience with both document/NoSQL stores (</span><span data-markdown-start-index="4129">MongoDB</span><span data-markdown-start-index="4138">) and relational engines (</span><span data-markdown-start-index="4166">PostgreSQL</span><span data-markdown-start-index="4178">).</span></p> </li> <li> <p><strong><span data-markdown