Backend Engineer, Enterprise AI

Role: Backend Engineer, Enterprise AI

Location: New York City, Madison Square Park area

Reports to: Head of Engineering, Enterprise AI

Experience Level: 6+ years

Work Model: Hybrid, with regular in-office presence

Why Join Enterprise AI?

Enterprise AI is building the platform that enables enterprises to deploy and operate AI systems in production.

As a Backend Engineer, you will build the services and APIs behind the platform, including agent orchestration, model routing, enterprise integrations, identity and permissions, evaluation systems, and usage metering.

You will help harden the platform for multi-tenant, enterprise-grade operation while building features that allow customers to configure and operate AI systems with greater independence.

As a Backend Engineer, You Will

Build Core Platform Services

Design, build, and operate backend services and APIs that support agent orchestration, model routing, enterprise integrations, permissions, evaluation, and usage metering.

Build Reliable LLM Applications

Develop production systems using tool use, agent loops, retrieval, prompt versioning, and agent versioning.

Enable Enterprise Integrations

Build and maintain integrations with document stores, ticketing systems, data platforms, and other enterprise systems.

Build Secure Multi-Tenant Systems

Design data models, identity systems, permissions, and service boundaries that support secure operation across multiple tenants.

Own Features End to End

Take features from architecture through implementation, testing, deployment, observability, and ongoing operation.

Build for Reuse and Scale

Create connectors, services, and agent capabilities that can be reused across customers rather than rebuilt for each deployment.

The Anti-Sell

Production engineering, not prototyping: This is not a role for someone whose experience is limited to notebooks, demos, or early prototypes. You must have owned production software.

Backend depth: You will work on services, APIs, asynchronous job systems, identity, permissions, and integrations.

Enterprise complexity: The platform must support multi-tenant operation, enterprise identity systems, customer data permissions, and complex integrations.

End-to-end ownership: You will be expected to own meaningful backend product surfaces from design through production operation.

Our Backend Engineers Typically Have

Production backend experience: Six or more years as a backend or full-stack engineer working on production SaaS or enterprise platforms.

Strong services engineering: Deep experience with Python or TypeScript services, API design, asynchronous job systems, and production operations.

Enterprise identity and permissions: Hands-on experience with OAuth, OIDC, SAML, or SCIM, as well as multi-tenant data modeling and access control.

LLM application experience: Experience building production LLM features involving tool use, agent loops, retrieval, prompt versioning, or agent versioning.

Enterprise integration experience: Experience integrating with document stores, ticketing systems, data platforms, or other enterprise systems.

Production LLM ownership: A track record of shipping LLM features used by paying customers and owning production systems after launch.

Candidates whose experience is limited to notebooks or prototypes, or who have no multi-tenant or production ownership experience, will not be a fit for this role.

Top-Tier Candidates Will Have

Experience working on agent framework internals.

Experience implementing SOC 2 or similar controls.

Experience building integrations for financial services or other regulated industries.

Experience building on OpenAI or Anthropic APIs in a production environment.

Values