Senior AI Systems Architect

Jerry.ai•New York, NY

3d•$160,000 - $210,000•Remote

About The Position

Join a YC-backed, profitable Series C startup with capital and over 5M+ customers. This role offers the opportunity to own the AI systems layer of a consumer product used by millions, focusing on LLMs, agents, and internal APIs applied to a fragmented $2T market. You will work with partners like OpenAI to integrate Jerry.ai services directly into the ChatGPT App and pioneer new model capabilities. The company has a flat organization, ambitious goals, and a direct line to the founders and execs. The technical challenge lies in the system around AI, including agent capabilities, system integration, guardrails, and handling non-deterministic outputs. Jerry is building the first AI-powered advisor to manage all physical assets, starting with cars and expanding into new verticals like home, motorcycle, RV, and boat. The company has a proven track record with its own infrastructure automating sales and service conversations, handling over 50,000 chats a month. This role requires someone to manage a fast-moving, high-volume chatbot operation and contribute to future bets in voicebot, computer use, and consumer AI applications.

Requirements

5+ years in a product engineering or forward deployed engineering, ideally in an early stage startup
A track record of turning ambiguous problems into systems that actually run
Hands-on experience putting LLM-based systems into production, including the unglamorous parts: evals, regressions, latency, cost, and failure handling

Responsibilities

Decide what we build next in AI, and make the case for it.
Partner with OpenAI to evaluate and deploy next-generation voice models and workflow automation.
Evaluate emerging AI technology (voicebot, computer use agents, and beyond), prototype what's worth building, and make the call on what we invest in next.
Design evaluation frameworks and guardrails, and make the real tradeoffs between latency, cost, and accuracy in a regulated production environment.
Set the technical bar for our chatbot systems — shape what the prompt engineering team builds next and keep the architecture sound as it scales.
Build new automations across areas like record disputes, email/callout reduction, document validation (ex. licenses, proof of insurance).
Work directly with subject matter experts to turn domain knowledge into systems that behave correctly.