Decagon is looking to build the foundational data architecture for an AI-native product that enables companies to understand customer conversations with AI agents and improve agent performance.
Requirements
- 5+ years of experience building production-grade data pipelines and distributed data systems
- Expert proficiency in Python, SQL, and data orchestration tools (Airflow, Dagster, Prefect, and other similar tooling)
- Strong understanding of data modeling, specifically for analytics and complex querying needs
- Experience working with unstructured or semi-structured data at scale
- Ability to own large technical projects from architectural design to production deployment
- Experience designing feature stores for machine learning applications
- Experience working with OLAP databases like Clickhouse
Responsibilities
- Design and build scalable data pipelines that ingest, process, and structure millions of customer conversations (text and audio) in near real-time
- Architect and maintain feature stores that power workflows and products like Watchtower, Ask AI, and the rest of our analytics suite
- Develop the data foundation for our analytics platform, enabling deep queries into customer intent, sentiment trends, and agent performance
- Collaborate with Product and Engineering teams to translate complex product requirements into efficient, long-term data architecture solutions
Other
- In-office company
- Customers are everything, relentless momentum, winner’s mindset, and stronger together values
- Experience making data-driven and user-driven decisions to shape product direction
- Experience designing actionable insights that help users understand complex behaviors
- Experience working with LLM applications or agentic systems
