Senior AI Engineer

CalliereNew York, NY

About The Position

Our client backs and builds AI-native ventures from the ground up, and they're looking for a Senior AI Engineer who wants to be a core builder, not employee #400. You'll take validated concepts and turn them into real products with real users, then keep going as those products find their footing. If you've shipped end-to-end AI systems to production, built things nobody asked you to build, and want genuine ownership in what you create, keep reading. You're probably a strong engineer from a demanding technical environment with an entrepreneurial itch. Someone who's tired of incremental work on someone else's platform and wants to see their own fingerprints on something that ships.

Requirements

  • Several years of experience at an environment known for engineering rigor. A top quantitative trading firm or a high-bar technology company, with individual output you can clearly point to as your own
  • A track record shipping AI systems to production and operating them after launch: real users, real failure modes, a real post-launch story. Not demos, notebooks, or research prototypes.
  • A visible entrepreneurial streak: a side project, a startup, a founding or early role, or a genuine 0→1 effort inside a larger org. Evidence you don't just execute what's handed to you.
  • A STEM degree (CS, Math, Physics, Engineering) from a strong program.
  • Commercial EQ: you can hold your own with non-technical stakeholders, customers, and partners, not only other engineers.

Nice To Haves

  • Engineers from AI-native startups, or founding/early engineers who've shipped real product to real users
  • Quant or quant-adjacent engineers with an entrepreneurial background who want to move into building product

Responsibilities

  • Build end-to-end agentic AI systems: agents, retrieval, orchestration, tool integrations. From a blank repo through product-market fit
  • Take a product from rough scope to shipped, cutting hard to the smallest version that proves value, then hardening it for production
  • Pull reusable patterns and primitives out of each build so the next one starts further down the road
  • Work shoulder-to-shoulder with product and design partners to shape what gets built, not just how
  • Move fluidly across very different product contexts, and treat ambiguity as the job rather than an obstacle
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service