Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®. As a Software Engineer on this team, you’ll help design and build the foundation and applications around AI for data practitioners, working on search, information retrieval, and AI challenges.
Responsibilities:
- Shape the future of AI for data engineering - 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
- Push the boundaries of applied AI - experiment with LLMs, embeddings, and cutting-edge retrieval techniques to create developer tools that deliver insights to you and our customers
- Turn research into reality - 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, leveraging Astronomer’s unparalleled visibility into data pipelines across industries
- Influence the technical vision and architecture for the next generation of AI-driven data products
- Represent Astronomer in the community - through open-source contributions, technical talks, and publications that showcase our leadership in AI and data innovation
Requirements:
- 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
- Experience with LLMs, vector databases, embeddings, or other applied AI areas—or a strong desire to dive in
- 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
- A passion for AI systems for data, developer tools, or machine learning infrastructure
- Familiarity with Apache Airflow or other orchestration tools
- Demonstrated contributions to open source projects
- Experience in search, IR, or large-scale data infrastructure
- Exposure to early-stage startups or R&D organizations where ambiguity is the norm