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Open nowPosted 16 hours ago

AI Deployment Engineer/Manager

Safari AI9 open roles

Where
United States (Remote)
Work mode
Remote
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Your applicationOpen nowAI Deployment Engineer/ManagerSafari AI · United States (Remote)

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted 16 hours ago

The posting

About Safari AI

Safari AI's vision is to Automate Action of the leading companies in the physical economy, from Entertainment, Live Venues, QSR's, Retail and beyond. The company uses computer vision AI to Measure, Alert and provide AI-generated Recommendations at the operations of leading enterprises such as Merlin/Legoland, 7-11, Tanger Outlets, Charlotte Hornets, Tennessee Titans, and more.

Leadership & Culture

Safari AI is founded by Ali Vahabzadeh, who has a meaningful exit under his belt and has managed large, high-performing Go To Market and Engineering teams. The company is headquartered in Miami with the Engineering team co-located in Vancouver.

About You And How You Succeed At Safari AI

You're excited to build a product and invent a market that hasn't existed before. You read documentation first and are not afraid to ask for help when uncertain. You're looking to take ownership/run a singular project and take advantage of the freedom and culture an early stage startup can provide. You are looking to see through the fluff of the modern AI landscape and explore new ways of achieving measurable ROI. Enjoy a small team size ~10, project team of 1-3.

About the Role

We're hiring an AI Deployment Engineer/Manager to bring Safari AI's computer vision system to life at theme parks, stadiums, retail stores and live venues. You'll report to the Deployment lead and work alongside our ML and Engineering teams. This is forward-deployed work: cameras, edge computers, networks and servers, from the first site survey to a live, monitored system.

You'll get real ownership quickly. In your first 90 days you'll run parts of deployments with support from the team. By month six you'll own smaller deployments and pilot kits yourself. After about 12 months, a successful hire can grow into a senior Deployment Engineer, Solutions Engineering or Client Success role.

This role is remote within the U.S., with regular travel to customer sites.

What You Will Be Doing

  • Hardware Provisioning & Linux Administration: Set up and configure edge computers (x86 GPU servers and NVIDIA Jetson), cameras, network switches and 5G/LTE modems before they ship. Maintain, patch and troubleshoot Linux systems in the field, and improve our install scripts and Ansible playbooks.
  • On-Site Deployment & Implementation: Travel to customer sites to install and connect cameras and edge devices, verify camera streams and angles, and bring systems online. Work with installation contractors and customer IT teams to keep rollouts on schedule.
  • Solution Design (with the Deployment lead): Run pre-deployment assessments covering camera inventory, network layout, bandwidth sizing, redundancy and rack space. Help spec ML/GPU hardware and design site-to-site and VPN connections.
  • Project Coordination: Track hardware inventory, order from preferred vendors, coordinate shipping, and keep checklists, timelines and status reports current.
  • Customer Support & Monitoring: Be a technical point of contact for customers during and after deployment. Respond to alerts such as an offline camera or edge device, and resolve or escalate issues with clear notes.
  • Documentation & Automation: Write installation guides, SOPs and handoff documents, and use AI tools and scripts to automate repetitive deployment and support work.

What We're Looking For

  • A degree in Computer Science, Computer/Electrical Engineering, Information Technology or a related field, or equivalent hands-on experience
  • 0–3 years of experience in IT, system administration, network support, field engineering or a similar role (internships, co-ops and homelab projects count)
  • Comfortable on the Linux command line: SSH, permissions, services, logs and basic shell scripting
  • Basic networking: IP addressing, subnets, DHCP, DNS, switches and PoE
  • Comfortable with physical hardware: racking a server, running and testing cable, mounting and aiming a camera, working on a ladder
  • Strong troubleshooting habits: you narrow a problem down step by step and write down what you tried
  • Clear written and verbal communication with teammates, contractors and customer IT staff
  • Organized, detail-oriented and a fast learner in new technical environments

Bonus Points

  • Experience with IP cameras, NVR/VMS systems or RTSP streams (Axis, Hanwha, Hikvision and similar)
  • Experience with NVIDIA Jetson, GPUs or other edge AI hardware
  • Ansible, Docker, OpenVPN/WireGuard or other automation and remote-access tools
  • CompTIA Network+, CCNA or a homelab you can tell us about
  • Consulting, robotics or computer vision experience
  • You've built or used an AI agent to automate your own work

Additional Requirements

  • Must be permanently authorized to work in the U.S. (e.g., U.S. citizen or green card holder). We are unable to sponsor or take over sponsorship of work visas, now or in the future.
  • Able to travel regularly to customer sites, sometimes on short notice
  • Willing to work evenings and weekends when sites are closed to guests, and to respond to emergencies on priority projects
  • Able to lift and carry up to 50 lb of equipment

Why bet on Computer Vision and Safari AI?

  1. Huge opportunity hiding in plain sight: leveraging already-installed cameras to automate and real-time action on operational data
  2. Already the market leader in enterprise CV by working with industry leaders with billions in revenue
  3. Large chasm between customer knowledge and market availability, i.e. customers don't know what is available in the market...yet.
  4. Early leader in computer vision; everyone is small and unbranded (i.e. no Amazon or Google in the room to compete with)
  5. Very modular, allowing Safari AI and its customers to invent whole new use cases on a regular basis
  6. Developed the tech and data pipelines over three years and invested several million dollars and is now ready to scale
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