Basis equips accountants with a team of AI agents to take on real workflows. The company has hit product-market fit, has more demand than it can meet, and just raised $34m to scale.
Requirements
- Build and standardize our data platform
- Model the domain as a system
- Lead through clarity and technical excellence
- Own the architectural vision for your area and keep it consistent over time.
- Run effective design reviews that challenge assumptions and drive alignment.
- Mentor engineers on how to think about systems: from load testing to schema design to observability patterns.
- Simplify aggressively—removing accidental complexity and enforcing clean, stable abstractions.
Responsibilities
- Design data pipelines that ingest, validate, and transform accounting data into clean, reliable datasets.
- Define schemas and data contracts that balance flexibility with correctness.
- Build validation, lineage tracking, and drift detection into every pipeline.
- Create interfaces that make data discoverable, computable, and observable throughout the system.
- Translate accounting concepts into well-structured ontologies: entities, relationships, and rules.
- Create abstractions that help AI systems reason safely about real-world constraints.
- Design for clarity: make complex workflows understandable through schema, code, and documentation.
Other
- Own projects completely from scoping to delivery.
- Be the Responsible Party (RP) for the systems you design.
- Plan your own projects, work closely with your pod, and take full responsibility for execution and quality.
- Build systems that serve every part of Basis: AI, product, and internal agents.
- Make those systems fast, reliable, and easy to understand.
