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Edge Systems Jobs in Texas (NOW HIRING)

Rabot Inc

Systems Engineer

Arlington, TX · On-site

The real-time pipeline: cameras, on-device AI models, video processing, edge compute, and the systems that tie it all together. This is the layer between the physical world and our AI. You'll work ...

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How much do edge systems jobs pay per year?

As of Aug 28, 2026, the average yearly pay for edge systems in Texas is $63,760.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $79,200.00 per year, depending on experience, location, and employer.

What is an edge systems job?

An Edge Systems job involves managing and optimizing computing resources at the network edge, closer to end-users or data sources. Professionals in this role work with edge devices, cloud integration, security, and real-time data processing to improve system performance and reduce latency. Responsibilities may include deploying edge architectures, troubleshooting hardware/software issues, and ensuring seamless connectivity between edge and central systems. This role is critical in industries like IoT, telecommunications, and autonomous systems, where real-time data processing is essential.

What are the typical daily responsibilities of an edge systems professional?

Edge Systems professionals often focus on designing, deploying, and maintaining edge computing infrastructure that supports real-time applications close to data sources. Their daily tasks may include monitoring system performance, troubleshooting connectivity or security issues, and implementing software or firmware updates. They frequently collaborate with cloud architects, network engineers, and operations teams to optimize system reliability and meet business requirements. This dynamic environment makes every day unique, offering continued learning and the opportunity to have a direct impact on technological innovation within the organization.

What are the key skills and qualifications needed to thrive in the edge systems position?

To thrive in an Edge Systems role, you need a solid background in computer engineering or IT, combined with expertise in edge computing architectures, networking, and system integration. Hands-on experience with platforms such as Kubernetes, Docker, Azure IoT, and certifications like CompTIA Network+ or Cisco CCNA are commonly sought by employers. Analytical problem solving, strong communication, and the ability to work collaboratively with cross-functional technical teams greatly enhance success in this position. These skills ensure reliable deployment and maintenance of distributed edge solutions, which are critical for real-time data processing and operational efficiency.

What are the most commonly searched types of Edge Systems jobs in Texas?

The most popular types of Edge Systems jobs in Texas are:

What are popular job titles related to Edge Systems jobs in Texas?

For Edge Systems jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Edge Systems jobs in Texas look for?

The top searched job categories for Edge Systems jobs in Texas are:

What cities in Texas are hiring for Edge Systems jobs?

Cities in Texas with the most Edge Systems job openings:

Edge Systems jobs near you
Infographic showing various Edge Systems job openings in Texas as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $63,760 per year, or $30.7 per hour.

Systems Engineer

Arlington, TX • On-site

Rabot Inc
Trucking • 1 - 10 employees
Learn more about Rabot Incexternal

Full-time

Posted 8 days ago

Job description

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 push the real-time systems further.
The role
You'd work on the software that runs on and around our hardware. The real-time pipeline: cameras, on-device AI models, video processing, edge compute, and the systems that tie it all together. This is the layer between the physical world and our AI.
You'll work closely with our hardware engineer on the full perception and processing stack. Latency matters. Reliability matters. These systems run in warehouses, not data centers, and they need to work every time.
3+ years of experience required. We care less about where you worked and more about what you've built and how it performed.
In-person in Arlington, TX. Not remote.
What you'll do
  • Build and optimize real-time software systems. Video pipelines, inference engines, edge processing, device communication.
  • Write performant code for critical paths and scripting for tooling, orchestration, and model integration.
  • Work with the hardware team on the full stack from camera to cloud. You'll understand the hardware constraints and write software that respects them.
  • Profile and optimize. Latency budgets, memory constraints, CPU/GPU utilization on edge devices. You measure before you guess.
  • Ship reliable software to devices running in warehouses. These aren't dev environments. They need to run for months without intervention.
  • Improve deployment, testing, and monitoring for edge systems.
Who you are
  • You have 3+ years of experience writing software for systems that run in production. Not just scripts. Real systems with real performance requirements.
  • You understand real-time constraints. You've worked on software where latency and throughput actually matter, not just on paper.
  • You're comfortable close to the hardware. You don't need to design PCBs, but you understand device constraints, communication protocols, and what happens when software meets the physical world.
  • You can debug across layers. When something is slow or broken, you can trace it from application code down to system-level issues.
  • You write code that runs unsupervised. Edge systems can't crash and wait for someone to restart them.
  • You figure things out. Niche hardware, undocumented APIs, weird edge cases in warehouse environments. You dig in.
Nice to have
  • Experience with computer vision or perception systems. Camera calibration, image processing, video encoding/decoding, inference pipelines.
  • Background in robotics or autonomous systems. You've built software that interacts with the physical world in real time.
  • Experience with edge compute platforms and AI accelerators.
  • You've worked with AI/ML model deployment on device. Model optimization, quantization, inference runtimes.
  • Linux systems programming.
  • Experience shipping hardware products. You know the difference between a demo and a deployment.
What we offer
  • Base salary plus equity. A real stake, not a token grant.
  • You'd build the real-time systems at the core of a product that's deployed and working in warehouses today.
  • Direct access to founders and the hardware team. No layers between you and decisions.
  • Hard problems. Real constraints. Software that has to work in the physical world.
  • 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 where your engineering directly determines product quality, this structure works.
How to apply
Send us two things:
  1. A system you've built or worked on where performance mattered. What were the constraints, what tradeoffs did you make, and how did it perform?
  2. You have a camera feed, an AI model running on an edge device, and results need to reach a dashboard with minimal latency. Walk us through your architecture. Keep it under a page.
Rabot logo

About Rabot

Sourced by ZipRecruiter

Industry

Trucking

Company size

1 - 10 Employees

Headquarters location

San Francisco, CA, US

Year founded

2018

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