Founding AI Backend Engineer for Data Pipelines

Mason; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Mason, a rapidly growing tech company in San Francisco, is building a company brain by turning decades of fragmented documents, databases, emails, and operational knowledge into connected data for AI agents.

You will design and build backend systems to ingest, organize, connect, and retrieve enterprise information, ensuring accuracy and context for AI tasks. This role blends backend engineering, data architecture, and experimentation.

Qualifications

• Four+ years of engineering ownership on production backends, data platforms, or complex data integrations.
• Strong programming and SQL skills with emphasis on system design and data modeling.
• Experience maintaining pipelines as sources, schemas, and volumes evolve.
• Comfort with messy, heterogeneous data and real-world problem solving.
• Ability to test approaches on real data and turn experiments into dependable systems.
• High ownership, curiosity about data work improving downstream product.

Responsibilities

• Turn fragmented company data into a trusted company brain for AI agents.
• Design and build backend systems to ingest, organize, connect, and retrieve knowledge.
• Own production pipelines and processing infrastructure with strong data modeling.
• Develop parsing, extraction, deduplication, and reconciliation for real-world data.
• Create storage, indexing, and retrieval systems preserving sources and access control.
• Implement observability to measure extraction quality, freshness, latency, and cost.
• Scale architectures to billions of rows and large document collections while enabling updates.

Skills

Backend engineering

Data pipelines

System design

SQL

Python

TypeScript

Data modeling

Knowledge graphs

Tools

PostgreSQL

Snowflake

Databricks

Amazon Redshift

dbt

LangGraph

Retrieval and memory

pgvector

Job description

Mason, a rapidly growing tech company in San Francisco, is building a company brain by turning decades of fragmented documents, databases, emails, and operational knowledge into connected data for AI agents.

You will design and build backend systems to ingest, organize, connect, and retrieve enterprise information, ensuring accuracy and context for AI tasks. This role blends backend engineering, data architecture, and experimentation.