TextQL is an NYC-based startup working to drive the unit cost of a data-driven decision down to zero. Customers like Amazon, Ring, Scale AI, Lumeris, and the NBA rely on us to make better decisions, faster. We're rapidly expanding our engineering team to build the agentic data lakehouse – finding trustworthy answers to hard questions from messy enterprise data without configuring schemas, moving data, or lengthy implementation roadmaps.

Platform

Have you rage-quit a BI tool because the semantic layer couldn't handle a simple hierarchy? Have you built a semantic layer yourself?

Today, no one stakes their job on AI-generated queries. You'll build the system that changes that—giving agents the context to query enterprise data correctly, and the guardrails to prove it.

What Success Looks Like

• Within 90 days, you'll have shipped meaningful contributions to the platform layer
• Within 6 months, you'll own major subsystems end-to-end
• Within a year, you'll be a technical leader shaping the architecture of the agentic data lakehouse

About You

• 4+ years of experience as a data systems, backend, infrastructure, or platform engineer
• Experience at early-stage startups or building products from zero to one
• Comfortable diving into any part of the system—infrastructure, services, or frontend
• You care about building systems that are robust, scalable, and easy to use

Compensation & Logistics

• Total Compensation: $350K-450K ($200K base + $50K-150K bonus + $100K equity)
• Interview: We prefer on-site interviews when feasible and can make a decision within 72 hours of your on-site. If you're outside NYC, we'll cover all travel expenses.
• Onsite: We are 5 days a week in-office in FiDI, NYC
• Benefits: 401(k) matching up to 5%, top-tier health insurance, 21 days PTO, free lunch
• Visa Sponsorship: Yes—we retain immigration counsel to support the process.

If this description resonates, we strongly encourage you to apply.

The Application

We have a very simple, signal-driven process. Please send Gabriel an email with the following:

• What is the most significant technical challenge you have solved? How did you solve it?
• Your GitHub and/or LinkedIn
• Your resume