What you get to do
- Shape the future of AI for data engineering by building 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 by experimenting with LLMs, embeddings, and cutting-edge retrieval techniques to create developer tools.
- Turn research into reality by working 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.
What you bring to the role
- 5-8 years of software engineering experience with Python or Go.
- 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.
Bonus points if you have
- 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.
- Experience building out agentic systems on top of frontier models.
Compensation
The estimated total compensation for this role ranges from $200,000 - $230,000 based on leveling and geography, along with an equity component and a comprehensive benefits package.