Business Systems Engineer (Remote)

Business Systems Engineer

Location: Remote

Compensation: $2000 USD / month

Frank Darling designs custom engagement rings, and our software platform makes the operational complexity of that business work at scale.

A single diamond can be available from a supplier, listed on our website, shown to a client, reserved for an appointment, priced into a ring, or routed into production - and every system needs to agree on what is true. Our goal is to keep inventory, pricing, orders, and internal workflows accurate, reliable, and easy for teams to use.

We’re looking for an engineer who enjoys working at the intersection of software, operations, and business process. You should be comfortable with ambiguity, good at translating messy real-world workflows into maintainable systems, and confident making thoughtful judgment calls when there isn’t a perfect answer. You’ll work closely with non-technical stakeholders, so strong communication and documentation matter as much as the code itself.

We value autonomy, practical engineering, clear ownership, and systems that keep working long after they ship.

What You’ll Do

As a Business Systems Engineer, you will help build and operate the systems that connect our e-commerce, inventory, sales, client care, production, and gemology workflows. You’ll work on supplier data pipelines, Shopify integrations, pricing logic, internal tools, event-driven automations, and AI-assisted workflows that support teams across the company.

Some of the systems you’ll help build and maintain include:

Inventory pipelines importing hundreds of thousands of records from dozens of suppliers

Shopify integrations and order orchestration

Internal tools used across Sales, Client Care, Production, and Gemology

Pricing engines and business rules that drive our catalog

Event-driven workflows running on AWS

AI-assisted automation and internal tooling

Monitoring and operational tooling that keeps the platform healthy

Data integrations between SaaS platforms, internal systems, and production workflows

You’ll spend as much time understanding the business as you do writing code.

How You’ll Know You’ll Like This Job

This role is probably a good fit if:

You enjoy turning conversations into software.

You ask “why?” before you ask “how?”

You’re comfortable with ambiguity. Business problems rarely arrive as complete requirements, and you’re excited to untangle them.

You enjoy making thoughtful judgment calls. There usually isn’t one “correct” solution - just tradeoffs.

You’re technology-agnostic. Whether the right answer is Python, SQL, an AWS Lambda, an automation, or changing the business process itself, your goal is solving the problem well.

You believe documentation is part of engineering.

You get satisfaction from building systems that quietly do their jobs for years.

What Makes Someone Successful Here

We’re less interested in checking every box than finding someone who enjoys this style of engineering. We’re open to a range of experience levels, from strong mid-level engineers to senior candidates; scope and compensation will reflect experience.

Required

2+ years writing production Python

Working knowledge of JavaScript, SQL, Bash, and GraphQL

Experience designing, consuming, or debugging REST APIs

Familiarity with AWS Lambda and ECS

Experience working with relational databases

Comfortable debugging production systems

Comfortable reading and improving an existing codebase

Experience using Git in a collaborative development environment

Strong written communication and documentation skills

Comfortable working directly with non-technical stakeholders

Experience using Claude Code, Codex, or similar AI coding agents as a core part of your development workflow

AI-Assisted Development

AI isn’t an optional productivity tool here. It’s part of how we build software.

You should already be using Claude Code, Codex, or similar coding agents as a core part of your development workflow - not simply as autocomplete. We expect engineers to delegate implementation, investigation, refactoring, testing, and documentation to AI agents, critically review their output, and know when to trust them and when not to.

Nice to Have

Docker

AWS SQS, DynamoDB, RDS, S3, API Gateway, CloudFront, or IAM

Shopify APIs

ETL or large-scale data integration pipelines

Monday.com, Make.com, Trello, Zapier, or similar workflow platforms

Google Apps Script

Google Sheets automation

Monitoring, alerting, or operational tooling

E-commerce, inventory, manufacturing, or retail operations systems

Experience integrating LLMs into production workflows

How We Work

We trust engineers to make decisions.

You’ll work directly with the people running the business, ask questions, propose alternatives, and choose solutions that balance simplicity, reliability, and long-term maintainability. We value good judgment over rigid process, thoughtful tradeoffs over cleverness, and documentation over tribal knowledge.

You’ll have a great deal of autonomy, but you won’t be working in isolation. We believe the best engineering comes from understanding the business deeply, collaborating with the people closest to the problem, and building systems that make everyone’s work easier.

What Success Looks Like

Within your first 30 days

You’re shipping production code into existing systems.

You’re fielding requests from stakeholders and helping turn them into clear next steps.

You’re using documentation, code walkthroughs, and working sessions to build context quickly.

You’ve diagnosed and fixed issues with support from the team.

You’re beginning to understand how inventory, pricing, orders, and internal workflows connect across the business.

Within 90 days

You’re independently owning small to medium projects from discovery through deployment.

Business stakeholders are bringing you problems, not just implementation requests.

You’re making thoughtful technical decisions and explaining your reasoning clearly.

You’re comfortable debugging production issues across unfamiliar parts of the platform.

You’ve improved the reliability, clarity, or maintainability of systems you inherited.

Within six months

You’re leading larger projects that affect multiple teams or systems.

You understand the business well enough to identify better solutions than the original request.

You’re helping shape technical direction, not just executing known work.

You’ve built or materially improved systems that people across the company rely on every day without thinking about them.