> Markdown version of [/jobs/ext/2514211-software-engineer](https://www.wearedevelopers.com/jobs/ext/2514211-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Astronomer, Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $210,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Big Data, Programming Tools, Python (Programming Language), Machine Learning, Software Engineering, Large Language Models, Free and Open-Source Software - **Published:** August 28, 2026 - **Apply:** https://www.dice.com/job-detail/d44dcc8c-3e65-48e3-85d2-d70df4072fcb ## About 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The Software Engineer 2030: From Coder To AI Orchestrator? - Patrick Schnell](https://www.wearedevelopers.com/videos/1825-the-software-engineer-2030-from-coder-to-ai-orchestrator-patrick-schnell) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)