Product Reliability Engineer (L1 Support & Software Engineering)

About Hopstack

Hopstack is a U.S.-based SaaS company building an omnichannel fulfillment operating system for warehouses, 3PLs, and brands. Our software powers receiving, inventory management, order processing, picking, packing, shipping, and integrations with platforms such as Shopify, Amazon, and major shipping carriers.

Our customers depend on Hopstack to run their daily warehouse operations. When something breaks, our engineers need to understand the problem, repair it safely, and make sure it doesn't recur.

The Role

We are hiring a hands-on engineer to own complex production issues during U.S. business hours while actively improving the product.

This is not a traditional BPO, help-desk, or ticket-escalation role. You will investigate the actual application code, troubleshoot database and API behavior, develop fixes, and contribute to our Support Zero initiative: making the platform increasingly self-service, reliable, and easier for customers to operate without assistance.

What You'll Do

• Own technical incidents from customer report through diagnosis, resolution, verification, and customer communication.
• Debug Node.js/TypeScript backend services, REST APIs, MongoDB queries, asynchronous workflows, and integrations.
• Write, test, and submit code fixes through Git pull requests, collaborating with the engineering team on review and deployment.
• Investigate inconsistencies involving orders, inventory allocations, picking, packing, serial numbers, and shipping labels.
• Build and execute approved database scripts and recovery runbooks with safeguards, validation, and auditability.
• Diagnose issues using application logs, error tracking, API responses, traces, and production monitoring.
• Identify recurring support requests and build permanent solutions such as self-service recovery actions, clearer errors, automated validation, and safer retries.
• Use AI coding agents to speed up investigation, root-cause analysis and fixes, and help turn repeated debugging steps into reusable AI-assisted runbooks.
• Contribute to performance improvements, workflow redesigns, automated tests, and operational tooling.
• Communicate directly with U.S. customers when technical explanations or incident updates are required.

What We're Looking For

• Approximately 3 to 6+ years of hands-on software engineering or advanced application support experience.
• Strong JavaScript/TypeScript and Node.js development ability.
• Hands-on use of AI coding tools in real work, or a clear willingness to learn them quickly. Tell us how you use them today.
• Sound judgement when checking AI-generated code and queries before they reach production data.
• Sound judgement when checking AI-generated code and queries before they reach production data.
• Practical MongoDB experience, including querying, aggregations, indexing, and safe data modifications.
• Ability to read unfamiliar code, reproduce bugs, trace root causes, and implement working fixes.
• Experience with REST APIs, integrations, Git, testing, and cloud-hosted applications.
• Strong spoken and written English, including the ability to explain technical incidents clearly to nontechnical customers.
• Previous experience supporting production SaaS or enterprise software.
• Willingness and demonstrated ability to work the U.S. overnight shift consistently.
• Advantages: React, AWS, Sentry, RabbitMQ, Temporal, Shopify integrations, shipping APIs, fulfillment software, and automation scripting.
• What Success Looks Like
• Within 90 days, you should be able to independently investigate most common production issues, contribute tested fixes, perform approved recovery procedures, and deliver improvements that eliminate recurring customer support requests.
• We value engineers who think beyond the immediate ticket and ask: "What can we change so this issue never requires human support again?"

How to Apply
Please share your resume, GitHub or relevant code samples where available, and a short description of a production incident you personally debugged and fixed. If you use AI tools in your engineering work, tell us briefly how they fit into your debugging process. We are particularly interested in what you changed in the code and how you prevented recurrence.