Tech Lead, Core Product Engine (Backend)

Jerry.ai•Toronto, ON

1d•Remote

About The Position

The Core Backend Team owns the most critical part of the "last mile" of Jerry.ai's insurance marketplace, orchestrating complex, multi-step transactions with external systems to finalize insurance policy purchases. This involves building custom orchestration layers to navigate internal and external interfaces due to the industry's lack of modern APIs. The challenge is to evolve current automation systems into a robust, fault-tolerant framework that can handle external interface changes gracefully and scale across dozens of new categories with minimal manual intervention. This role offers significant ownership, reporting directly to the co-founder/CTO, with a fast-paced environment and minimal red tape. The team is small but highly talented, with a focus on hands-on technical work (80% of the time) and leveraging a massive amount of customer data to guide decisions. The initial phase involves deep code involvement to understand the core product and lead refactoring of existing automation systems, designing new standards, and ensuring predictability and testability. The second phase will focus on an AI-first approach to build the next generation of internal tools to support user growth from 5 million to 50 million.

Requirements

Player Coach: Likely founded a company or were a lead architect at an early-stage startup.
Builder at heart, enjoys being in the trenches alongside the team.
Detective: Obsessed with success rates, hunting for edge cases in complex business logic.
Systems Thinker: High bar for system design, especially for offline, asynchronous jobs.
Understanding of async work requiring strict standards for decoupling, state management, and failure retry logic.
Experience with TypeScript (Nest.js, React), GraphQL, AWS (ECS/EKS, Lambda).

Responsibilities

Evolve current automation systems to a robust, fault-tolerant framework.
Handle external interface changes gracefully.
Scale automation systems across dozens of new categories with minimal manual intervention.
Lead incremental refactoring of existing automation systems.
Design and implement new standards for automation systems.
Pair with engineers to ensure the new system is predictable and testable.
Build the next generation of internal tools using an AI-first approach.