🛠 Tech Stack

💼 About This Role

You'll own the end-to-end data architecture for AI-first consumption, designing the foundation for GPT assistants, AI agents, and predictive models. You'll lead data modeling across all departments, build the contextual intelligence layer with RAG and vector stores, and ensure data quality for AI systems. This role sits at the intersection of data science, AI infrastructure, and data governance.

🎯 What You'll Do

• Design and govern the data warehouse for AI and BI consumption.
• Build RAG architecture, vector stores, and knowledge base pipelines.
• Own feature engineering strategy and feature store architecture.
• Establish AI data engineering standards and governance controls.

📋 Requirements

• 7–10 years in data engineering or architecture with 3 years focused on AI/ML data infrastructure.
• Deep expertise in Snowflake, dbt, Airflow, and ELT/ETL pipeline design.
• Experience designing data architecture for AI consumption (vector databases, RAG, feature stores).
• Strong data modeling skills across dimensional, normalized, and AI-optimized schemas.

✨ Nice to Have

• Experience with agentic AI frameworks like LangGraph or Mastra.
• Experience building production-scale RAG architectures.
• Experience in private equity-backed SaaS organizations.

🎁 Benefits & Perks

• 🏖️ Unlimited PTO
• 🏥 Comprehensive health insurance
• 📈 Stock options
• 💻 Remote-first culture
• 🏠 Home office stipend

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min