Software Engineer (DevOps & Deployment)
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AI Summary
You will deploy, configure, and maintain on-prem GPU servers while collaborating with casino IT teams to ensure system reliability. Additionally, you will contribute to core product development, manage containerization, and build automation scripts for seamless deployments.
Software Engineer (DevOps & Deployment)
Location: Las Vegas, NV / Remote (frequent on-site deployment)
Company: EagleSight.ai
Type: Full-time
About Us:
EagleSight.ai is building vision agents for large venues such as hotels and casinos— powering real-time video analytics and intelligent surveillance across hundreds of camera streams. Our systems run on-prem in some of the largest resorts in Las Vegas, and many more are in the pipeline.
The Role:
We’re looking for a hands-on Software Engineer (DevOps & Deployment) who can help us keep our systems running reliably in the field, while also contributing to core product development. You’ll wear multiple hats — configuring and managing GPU servers, supporting deployment of AI models, supporting backend code, and troubleshooting live systems alongside casino IT teams.
You Will:
- Deploy, configure, and maintain EagleSight’s on-prem GPU servers in casino environments. Our stack includes – Ubuntu, Python, NVIDIA acceleration (TensorRT, Triton), RabbitMQ, Postgres and React.
- Own containerization and remote monitoring for multiple sites.
- Work closely with our ML and full-stack engineers to ship on-site updates, improve reliability, and debug issues across the stack.
- Collaborate with casino IT/security teams to manage network access, firewalls, and system security.
- Build scripts and automation to make deployment, upgrades, and monitoring seamless.
- Proactively improve observability — health checks, logs, metrics, and alerting.
- Be the first point of technical contact for our customers in Las Vegas.
What We’re Looking For:
- 3+ years of experience in DevOps engineering roles.
- Strong Linux skills, Docker, networking, and performance debugging.
- Comfortable working in live production environments with minimal supervision.
- A startup mindset — resourceful, adaptable, and excited to work across ML, backend, and DevOps boundaries.
Nice to Have:
- Experience with GStreamer, FFmpeg, RTSP (or similar protocol) video pipelines.
- Integration experience with enterprise VMS software
- Experience with Prometheus/Grafana or similar monitoring stacks.
- Familiarity with GPU environments (NVIDIA drivers, CUDA, Triton, TensorRT).
Why Join Us:
You’ll be joining a small, fast-moving team where your work directly impacts live systems used in large venues every day. You’ll have ownership over real infrastructure, autonomy to ship fast, and the chance to grow along with a team that has gained strong traction in a short period of time.
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