{"id":4017633,"url":"https://alion.io/job/vivenu-senior-software-engineer-data-ai-platform-mwd","title":"Senior Software Engineer - Data & AI Platform (m/w/d)","company":{"id":39986,"name":"Vivenu","domain":"vivenu.com","url":"https://alion.io/company/vivenu","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":87,"open_postings":27,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":92,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Düsseldorf, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"ClickHouse","optional":false},{"name":"DuckDB","optional":false},{"name":"Function Calling","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-11-10T10:49:30Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T23:58:42Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"With over 10 million end users and usage quadrupling annually, our infrastructure now handles over 1 billion requests per month - 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.\nAs a Senior Software Engineer - Data & AI Platform (d/f/m) your responsibilities will include:\nYour Responsibilities:\nBuild Analytical Query Engines: Connect our transactional backends (MongoDB) with modern analytical event stores (ClickHouse) to support sub-second aggregations across millions of ticket transactions.\n\nImplement AI Retrieval & Reporting Workflows: 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.\n\nMaintain Low-Latency Reporting APIs: Write high-performance production services in Goor TypeScript/Node.jsthat power real-time reporting dashboards for global organizers without degrading transactional processing.\n\nCentralize Data Flows & Auditing: 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.\n\nSprint Scoping & Architecture: Collaborate directly in monthly in-person architecture sessions in Frankfurt alongside the VP of Engineering, CTO, and engineering leads to define technical milestones.\n\nWhat you will need to succeed in this role:\n5+ years of hands-on experience building high-throughput, distributed production services using Go, Python, or TypeScript/Node.js.\n\nAnalytical Warehousing Experience: Direct, hands-on production experience with ClickHouse(or closely related low-latency analytical engines like DuckDB, Snowflake, or Apache Pinot) for high-volume event streams.\n\nDatabase Mastery: Solid practical experience with both document/NoSQL stores (MongoDB) and relational engines (PostgreSQL).\n\nProduction AI / RAG Engineering: Proven experience deploying production RAG systems, function calling, evaluation frameworks, and supervisor architectures (e.g., LangGraph, LlamaIndex, or custom orchestration layers).\n\nEvent-Driven Architectures: Strong understanding of distributed message streaming using Kafka, RabbitMQ, or cloud pub/sub mechanisms.\n\nPragmatic Mindset: High autonomy and scrappiness-you choose reliable, deterministic validation layers and battle-tested databases over fragile AI hype.","description_format":"text","description_chars":2557,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Ticketing","Event 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