Astronomer is looking to build a global context layer for data to power search and discovery, code generation for data and analytics, and automated root cause analysis, leveraging LLMs and their unique vantage point of data movement across organizations.
Requirements
- Experience with LLMs, vector databases, embeddings, or other applied AI areas—or a strong desire to dive in.
- Familiarity with Apache Airflow or other orchestration tools.
- Demonstrated contributions to open source projects.
- Experience in search, IR, or large-scale data infrastructure.
Responsibilities
- build intelligent systems that understand, reason about, and optimize the flow of data across entire organizations.
- Design and engineer the brain of Astronomer’s context layer
- crafting components that power data modeling, semantic search, retrieval, and code generation.
- experiment with LLMs, embeddings, and cutting-edge retrieval techniques to create developer tools that deliver insights to you and our customers.
- work side by side with R&D and product teams to bring early AI concepts to life in the product experience.
- Solve high-impact information retrieval and search challenges at a global scale
- Influence the technical vision and architecture
Other
- Empathy for users, and a deep interest in improving the workflows of data professionals.
- Familiarity with early-stage product development; comfortable working with ambiguity in a fast-changing field.
- A creative, experimental mindset: you enjoy exploring uncharted areas, validating hypotheses, and learning through iteration.
- Strong collaboration and communication skills—you can explain complex systems clearly to both technical and non-technical audiences.
- A collaborative approach and comfort working in an evolving, research-driven environment where ideas move quickly.
