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Native Bridge
Open role

Senior AI Engineer

Engineering Remote (US / Canada) Full-time $165k to $210k + equity + profit share

About the role

We don't build demos. We ship AI systems that run in production and tie to a revenue number. As a Senior AI Engineer at Native Bridge, you'll own the hardest, most interesting part of that promise: turning ambiguous use cases into agents, RAG systems, and integrations that hold up under real load, inside the stack a client already runs.

This is a senior, high-autonomy role. You'll work directly with strategists and marketers on the same team, with no throwing specs over a wall, and you'll be in front of clients when it matters.

What you'll do

  • Design and ship agentic AI systems and LLM/RAG pipelines that survive contact with production traffic.
  • Integrate AI deeply into client stacks, including CRMs, warehouses, e-commerce platforms, and service-ops tools, using their real APIs and webhooks.
  • Build the data foundations and evaluation harnesses that make AI outputs trustworthy and measurable.
  • Own delivery end-to-end: from a paid diagnostic through a 30-day pilot to a scaled, monitored system.
  • Pressure-test use cases honestly, including telling a client when something isn't worth building.

What we're looking for

Must-haves

  • 5+ years building and shipping production software, with recent hands-on LLM/agent work.
  • Real experience integrating with third-party APIs (CRM, commerce, or data platforms).
  • Strong opinions on evaluation, observability, and error handling for non-deterministic systems.
  • Comfort owning ambiguity and talking to clients directly.

Nice-to-haves

  • Experience with Claude / Anthropic tooling, RAG architectures, or agent frameworks in production.
  • Background in data engineering or MLOps.
  • Prior agency, consultancy, or startup-founder experience.

Our stack

Claude Code, TypeScript / Python, Vercel, Snowflake / BigQuery, Linear, and Slack, plus whatever a client already runs (Salesforce, Shopify, Zoho, ServiceTitan, Klaviyo, and the rest of the ecosystem).

Process

  1. Intro call with the Engineering Practice Lead (30 min).
  2. A paid, scoped technical exercise that mirrors real work, with no whiteboard trivia.
  3. A working session walking through your solution and a past production system you shipped.
  4. Final conversation with the General Manager on fit and compensation.

We move fast and keep you informed at every step.