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Open nowPosted 207 days ago

Software Engineer

rabot6 open roles

Where
Arlington, TX
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On site
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Your applicationOpen nowSoftware Engineerrabot · Arlington, TX
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Early applications get read.

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  4. 13.4%14 days
  5. 34.5%30 days
This job: posted 207 days ago

The posting

ABOUT RABOT

Rabot builds vision AI for warehouse packing operations. Cameras watch the pack line, software figures out where things are slow or wrong, and operators get real-time feedback that actually changes how they work. Customers stick around because it measurably improves their output.

We're venture-backed with distribution partnerships with major industry players. The product works. Now we need engineers to build what's next.

THE ROLE

You'd work on the customer-facing product. The software that warehouse operators, managers, and executives interact with every day. Dashboards, real-time views, configuration, analytics, integrations. This is the layer between our AI and the people who use it.

The team is small. You'll ship features end to end: spec it out with product, build it, deploy it, and hear directly from customers whether it works. There's no handoff chain. You own your code from commit to production.

3+ years of experience required. We care less about where you worked and more about what you've built.

In-person in Arlington, TX. Not remote.

WHAT YOU'LL DO

- Build and ship features in the customer-facing product. Full stack: frontend, backend, cloud infrastructure.

- Work directly with product and customers to understand what needs to be built and why.

- Own what you ship. You deploy it, you monitor it, you fix it when it breaks.

- Write code that other people can read and maintain. The team is small and everyone touches everything.

- Improve the development and deployment pipeline as you go. CI/CD, testing, observability.

- Use AI tools in your workflow. We expect it. They're good at the boring parts.

WHO YOU ARE

- You have 3+ years of professional software engineering experience. You've shipped production software that real users depend on.

- You're strong across the stack. Not just tutorials. You've built and maintained real applications.

- You're comfortable with cloud infrastructure. Deploying, scaling, debugging production systems.

- You write clean code and you care about it, but you don't let perfect get in the way of shipped.

- You can work across the stack. Frontend one day, backend the next, infrastructure when it needs fixing.

- You communicate clearly. Small team means you talk to product, customers, and other engineers directly.

- You figure things out. When you hit something you haven't seen before, you dig in instead of waiting for help.

NICE TO HAVE

- Experience building B2B SaaS products. You understand multi-tenant systems, customer configuration, and the difference between consumer and enterprise software.

- You've worked with real-time data or video/image pipelines.

- Background in or exposure to computer vision, AI/ML, or IoT systems.

- Experience with warehouse, logistics, or industrial software.

- You've worked at a startup before and know what shipping fast with a small team actually looks like.

WHAT WE OFFER

- Base salary plus equity. A real stake, not a token grant.

- You'd build the product customers interact with every day at a company with clear traction.

- Direct access to founders and customers. Short feedback loops.

- AI tools and a team that uses them. We build AI products and we use AI to build them.

- A small team where your work is visible and your opinions matter.

COMP

We want someone who bets on themselves. If you're optimizing purely for guaranteed base, this probably isn't the right fit. If you want equity in a company you can directly make better with your code, this structure works.

HOW TO APPLY

Send us two things:

1. Something you've built that you're proud of. Could be a feature, a system, a side project, open source work. What was it, what decisions did you make, and what would you do differently?

2. You're designing a dashboard that shows warehouse managers real-time packing performance across many stations. What's your approach to keeping it fast? Keep it under a page.

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