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AstronomerAstronomerNew York, NY

Senior Software Engineer, Applied AI

Build applied AI systems for data engineering, including semantic search, retrieval, code generation, and agentic developer tools. The role requires strong software engineering and collaboration skills, plus experience or interest in LLMs, embeddings, vector databases, and information retrieval.

168k – 230k/yr
Hybrid5+ YOEAI Research

About the role

Responsibilities

  • Build intelligent systems that understand, reason about, and optimize data flows across organizations.
  • Design and engineer components for data modeling, semantic search, retrieval, and code generation.
  • Experiment with LLMs, embeddings, and retrieval techniques to create developer tools.
  • Translate applied research and early AI concepts into product experiences.
  • Solve information retrieval and search challenges at global scale.
  • Influence the technical vision and architecture for AI-driven data products.
  • Contribute to the technical community through open-source projects, talks, and publications.

Requirements

  • Empathy for users and interest in improving data professionals’ workflows.
  • Familiarity with early-stage product development and comfort with ambiguity.
  • Experience with LLMs, vector databases, embeddings, or other applied AI areas, or a strong desire to learn them.
  • Creative, experimental mindset with an iterative approach to validating hypotheses.
  • Strong collaboration and communication skills, including the ability to explain complex systems to technical and non-technical audiences.
  • Comfort working in an evolving, research-driven environment.

Nice-to-haves

  • Passion for AI systems for data, developer tools, or machine-learning infrastructure.
  • Familiarity with Apache Airflow or other orchestration tools.
  • Contributions to open-source projects.
  • Experience in search, information retrieval, or large-scale data infrastructure.
  • Experience in early-stage startups or R&D organizations.
  • Experience building agentic systems on frontier models.

Compensation and benefits

  • Estimated total compensation of $168,000–$230,000, based on leveling and geography.
  • Equity component and comprehensive benefits package.

Skills

LLMsVector DatabasesEmbeddingsinformation retrievalsemantic searchapache airflowPythonSQLmachine learning infrastructureOpen Source

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