Gen AI Engineer at ArangoDB, Remote (Global)

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Founded in Germany and now headquartered in San Francisco, ArangoDB is on a mission to make working with complex data simple, powerful, and AI-ready. Based in California and in Cologne (with a global team), we’re building a cutting-edge data platform that helps organizations bring all their data together — graph, document, key/value, full-text, and vector search — in one engine.

Why does that matter? Because it means developers and data teams can build next-gen AI applications like RAG, knowledge graphs, and smart agents — without gluing together a bunch of tools that were never meant to work together.

Our platform makes it easy to work with any kind of data-structured, semi-structured, or unstructured, and it gives teams everything they need to build faster, smarter, and with way more context. From our easy-to-learn AQL query language to modern integration tools, we’re here to help teams grow and scale with AI.

Sounds exciting? We think so too. Come join us and help shape the future of data.

About the Role

As part of our team, you oversee the technical development of ArangoDB’s capabilities within the GenAI universe. Your responsibilities include:

• Design and own Python-based features for ArangoDB’s Unified Platform
• Evaluate the latest developments and innovations in the GenAI and Python fields, applying them effectively in your work
• Build solutions for GenAI use cases such as data pipelines, retrieval-augmented generation (RAG), and advanced analytics
• Develop and refine agentic workflows: build, orchestrate, and optimize autonomous agents for complex tasks within distributed environments
• Integrate and manage private and cloud-hosted LLMs with a focus on secure, scalable deployment
• Build and scale ArangoDB solutions within Kubernetes environments, ensuring robust operation and performance for AI workloads.
• Other duties as assigned from time to time.

Your Skills

• At least 3 years of Python experience
• Strong foundation in software design and architecture, focusing on writing readable, maintainable, and production-grade code.
• Solid expertise in testing software across all levels, including unit tests, integration tests, and end-to-end testing strategies.
• Hands-on experience with NoSQL/SQL, Mac or Linux, Docker and Kubernetes
• Passionate about solving complex problems, using an analytical approach
• Bonus points for:
  • Experience with database systems and Data/ML ecosystem
  • Experience working with highly connected, complex systems, and the ability to mentally model and navigate intricate architectures
  • Experience with Cloud-native development (AWS, Kubernetes,…)
  • Open Source experience
  • Strong exposure to Machine Learning and Generative AI workflows
  • Background in working with or designing graph data architectures
  • Familiarity with deploying and integrating Large Language Models (LLMs), including private and cloud-based LLMs