The Role
Deploy, configure, and maintain on-prem GPU servers and containerized services for real-time video analytics. Manage deployments, monitoring, automation, and incident debugging; collaborate with ML/backend teams and casino IT to ensure secure, reliable production systems.
Summary Generated by Built In
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).
- Experience configuring and deploying AeroStream multiplexers.
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.
Skills Required
- 3+ years of experience in DevOps engineering roles
- Strong Linux skills (Ubuntu)
- Docker and containerization experience
- Networking knowledge and firewall/network access management
- Performance debugging in production environments
- Experience deploying, configuring, and maintaining on-prem GPU servers
- Experience with Python
- Experience with container monitoring and remote site monitoring
- Automation and scripting for deployment, upgrades, and monitoring
- Comfortable working in live production environments with minimal supervision
- Experience collaborating with enterprise IT/security teams
- Experience with RabbitMQ or Postgres (stack familiarity)
- Experience with React or working alongside full-stack teams
- Experience with GPU acceleration tooling (Triton, TensorRT)
- Experience with video pipelines (GStreamer, FFmpeg, RTSP)
- Integration experience with enterprise VMS software
- Experience with Prometheus/Grafana or similar monitoring stacks
- Familiarity with NVIDIA drivers and CUDA
- Experience configuring and deploying AeroStream multiplexers
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The Company
What We Do
EagleSight.ai develops on-premise Vision AI agents that transform passive CCTV surveillance into proactive profit and security protection. Utilizing advanced machine learning, AI, and computer vision technology, the company enables high-capacity venues, particularly major casino operations, to detect critical incidents, dealer errors, and cheating in real-time, significantly enhancing overall game protection and supporting efficient revenue recovery across their operations.
