Deployed Engineer, Enterprise Systems

Juul Labs•San Francisco, CA

About The Position

The Enterprise AI Systems team is responsible for the core business systems at Juul Labs, including ERP, HRIS, Quality & Regulatory, CRM, and IT Service Management. This role focuses on rebuilding how these systems are managed by treating system configuration as code, utilizing version control, testing, CI/CD pipelines, and AI coding agents. The Forward Deployed Engineer, Enterprise Systems position blends business systems knowledge, software engineering practices, and applied AI, functioning more like a DevOps or forward-deployed engineer than traditional IT support.

Requirements

5+ years of experience in enterprise systems engineering, DevOps, or business systems development.
Hands-on ownership of at least one major ERP, HRIS, CRM, Quality/Regulatory, or ITSM platform in a live production environment.
Solid working knowledge of data and process flow across enterprise systems, including understanding of ERP/HRIS data schemas and cross-system dependencies.
Hands-on experience building CI/CD pipelines and using Git for version-controlled deployments.
Experience with or strong interest in using AI coding agents or agentic engineering tools for production work.
Proficiency in SQL, with experience building automated test scripts and regression suites for large data sets.
Experience with API and integration technologies (REST, SOAP, EDI) and middleware tools.
Working knowledge of relevant compliance frameworks (SOX, ITGC).
Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders and vice versa.
BS degree in Computer Science or related engineering field, or equivalent experience.

Nice To Haves

Quality/regulatory system experience is a plus.

Responsibilities

Build Configuration-as-Code (CaC) for core enterprise systems (ERP, HRIS, Quality/Regulatory, CRM, ITSM) to enable version-controlled, tested, and software-like deployments.
Design and maintain CI/CD pipelines and Git-based workflows for business systems configuration and integration changes.
Build human-in-the-loop (HITL) review steps for validating AI-generated configuration and code changes before production deployment.
Evaluate and operationalize AI coding agents to accelerate configuration, integration, and regression testing, and identify areas for automation.
Build reusable, automated test scripts and regression suites for core business systems to reduce manual testing.
Design and maintain integrations between enterprise systems using REST, SOAP, EDI, and middleware tools.
Partner with stakeholders (Finance, Supply Chain, Quality/Regulatory, HR, Sales) to translate business requirements into automated, auditable system changes.
Maintain data integrity, security, and compliance (SOX, ITGC) across all automated pipelines and configuration changes.
Document system architecture, data flows, and pipelines for both technical and non-technical stakeholders.