> Markdown version of [/jobs/ext/1292142-remote-ai-engineer-knowledge](https://www.wearedevelopers.com/jobs/ext/1292142-remote-ai-engineer-knowledge). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Remote AI Engineer - Knowledge - **Company:** RoomPriceGenie - **Location:** Germany (Remote available) - **Salary:** €85,000.0 - €95,000.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Business Systems, Graph Database, Information Retrieval, Python (Programming Language), Knowledge-Based Systems, Metadata, Operational Databases, Cloud Services, Search Technologies, SQL Databases, TypeScript, Enterprise Search, Data Ingestion, Snowflake, Production Code, Data Pipelines, Automation Anywhere, Databricks - **Published:** July 16, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=55c959f257dfa6cd ## About the Role * Strong experience building and operating production data, search, or knowledge systems. * Excellent software engineering fundamentals, ideally in Python and/or TypeScript, APIs, data pipelines, and cloud services. * Experience with information retrieval, semantic search, RAG, knowledge graphs, document processing, or enterprise search. * Strong understanding of data modelling, metadata, lineage/provenance, data quality, and access-control patterns. * Heavy Notion advocate and user. * Pragmatic enough to use the right tool for the job; from no-code solutions to custom tooling. * Practical experience with SQL and modern data tooling; Snowflake, Databricks, Dagster, dbt, AWS, vector databases, and/or graph technologies are strong pluses. * Sound judgment about when structured data, search, retrieval, and human process each solve the problem best. * Comfortable working with ambiguous source material and partnering directly with non-technical domain owners. * You care about trust: accurate answers, traceable sources, safe permissions, and maintainable systems over impressive demos. * Fluent in English and based in the European time zone (UTC+0 to UTC+2). ## Description This is not a narrow RAG role. You will work across information architecture, data ingestion, retrieval, provenance, access control, and quality. Your first focus will be turning Notion into a reliable company memory while establishing the reusable platform patterns that support future AI workflows and agents. You will join the AI & Security team and work closely with domain experts, Security, Data, and Engineering. You will make the paved road easy: teams should be able to create useful AI workflows without recreating connectors, permissions, taxonomy, or evaluation from scratch. What You'll Do * Design and implement the knowledge architecture: taxonomy, content lifecycle, ownership, metadata, provenance, and correct-at-source workflows. * Build reliable ingestion and synchronization pipelines across Notion and approved business systems, with clear data quality and access-control standards. * Develop retrieval, search, and context-assembly services for internal AI experiences and production agents. * Establish evaluation for knowledge quality: coverage, freshness, retrieval relevance, groundedness, and failure modes. * Partner with teams migrating and structuring high-value knowledge; make good content practices practical rather than bureaucratic. * Build reusable components, documentation, and templates that allow departments to self-serve safely. * Work with Security and Architecture on permissions, PII boundaries, auditability, and governance-by-default. * Remain hands-on: write production code, review designs, diagnose data-quality issues, and improve operational reliability. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs](https://www.wearedevelopers.com/videos/1417-new-ai-centric-sdlc-rethinking-software-development-with-knowledge-graphs) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)