AI Engineer
About this role
About GlassFlow:
GlassFlow is the data infrastructure for AI agents in production. It has two products: GlassFlow Tares, which feeds agents correlated data from every system they touch, and GlassFlow Rius, which traces and debugs what agents do once they're running.
Requirements
- What we’re looking for
- You are:
- Strong software-engineering skills and experience building production systems.
- Practical experience working with LLMs, agents, retrieval systems, or applied machine learning.
- Proficiency in Python and familiarity with modern backend and data infrastruct
About GlassFlow
GlassFlow is the data infrastructure for AI agents in production. It has two products: GlassFlow Tares, which feeds agents correlated data from every system they touch, and GlassFlow Rius, which traces and debugs what agents do once they're running. We’re a Berlin startup with a Silicon Valley mentality, backed with $5.9m from Upfront Ventures, the CEO of GitHub, the ex-CTO of Aiven, and more world-class investors. The founders are serial entrepreneurs with more +10y of experience in building and selling data products. Tasks Why is this role special Design and build memory systems for AI agents. Improve retrieval, ranking, context assembly, and long-term memory. Develop systems for entity resolution, temporal reasoning, provenance, and knowledge representation. Build agent capabilities that combine reasoning with reliable tool use. Design evaluations for retrieval quality, agent behavior, and end-to-end task performance. Investigate failures using traces, datasets, and production feedback. Experiment with approaches such as semantic search, graph-based retrieval, reranking, trajectory analysis, and selective replay. Ensure agents retrieve and use information according to user permissions and organizational access controls. Improve the reliability, latency, and cost of AI systems in production. Collaborate directly with the founders and broader engineering team on product direction and architecture.