Deployment Engineer | Video Analytics

Samriddhi Automations Pvt. Ltd.; Hinoba-an; On-site; PHP 793,000 - 1,389,000; Full time

Job summary

Sparsh is deploying AI-driven video analytics solutions across cameras, edge devices, GPU servers, NVR/VMS platforms and customer systems. This role sits within the Software & VA team and connects AI software with customer sites.

You will install, configure, integrate and commission video analytics solutions while collaborating with customer IT teams, CV, QA and deployment stakeholders to bring projects live on time and to specification.

Qualifications

• 2–5 years of experience deploying software on Linux servers or embedded/edge devices.
• Diploma or B.Tech in Computer Science, Electronics, IT or equivalent.
• Strong Linux administration skills with Ubuntu.
• Understanding of networking fundamentals including IP addressing, VLANs, port forwarding, firewalls, VPN and PoE switches.
• Working knowledge of IP cameras, NVR/DVR, RTSP/ONVIF, video codecs and bandwidth/storage calculations.
• Bash and/or Python scripting experience for automation and troubleshooting.
• Excellent problem-solving and communication skills with willingness to travel to customer sites approximately 30–50%.

Responsibilities

• Plan and execute deployment of video analytics software including hardware sizing, OS and driver setup, container installation and configuration.
• Integrate RTSP/ONVIF camera streams, NVRs, VMS platforms and customer systems while validating bandwidth, storage and stream health.
• Configure camera calibration, ROI and line-crossing zones, ANPR lanes, face-enrolment databases, alert rules and notification channels.
• Build automation using Docker, Docker Compose, shell or Ansible scripts, image provisioning and remote update and rollback procedures.
• Set up health monitoring, VPN access and cybersecurity hardening while providing L2 support and diagnosing deployment issues after go-live.

Skills

Edge deployment

Linux administration

Networking fundamentals

Python scripting

Bash scripting

Docker

Ansible

Ubuntu

Education

Diploma/B.Tech in CS/Electronics/IT

Tools

Docker

Ansible

Ubuntu

NVR/DVR

RTSP/ONVIF

Job description

Noida, Uttar Pradesh (with travel to customer sites across India)

Noida, Uttar Pradesh (with travel to customer sites across India)

experience

2–5 years

function

Video Analytics | Deployment | DevOps

reporting_to

AI Product Manager / Head of Software VA

work_nature

Technical / Deployment-focused / Customer-facing

Where this role sits

Sparsh is deploying AI-driven video analytics solutions across cameras, edge devices, GPU servers, NVR/VMS platforms and customer systems.

This role sits within the Software & Video Analytics (VA) team and acts as the bridge between Sparsh's AI software and customer sites.

You will install, configure, integrate and commission video analytics solutions while working with customer IT teams, Computer Vision, QA and deployment stakeholders to bring projects live on time and to specification.

The role

This role is:

What you’ll work on

End-to-end VA Deployment

Plan and execute deployment of video analytics software including hardware sizing, OS and driver setup, container installation and configuration

Integrate RTSP/ONVIF camera streams, NVRs, VMS platforms and customer systems while validating bandwidth, storage and stream health

Configure camera calibration, ROI and line-crossing zones, ANPR lanes, face-enrolment databases, alert rules and notification channels

Build automation using Docker, Docker Compose, shell or Ansible scripts, image provisioning and remote update and rollback procedures

Monitoring & Field Support

Set up health monitoring, VPN access and cybersecurity hardening while providing L2 support and diagnosing deployment issues after go-live

Who this role is for

• 2–5 years of experience deploying software on Linux servers or embedded/edge devices
• Diploma or B.Tech in Computer Science, Electronics, IT or equivalent
• Strong Linux administration skills with Ubuntu
• Understanding of networking fundamentals including IP addressing, VLANs, port forwarding, firewalls, VPN and PoE switches
• Working knowledge of IP cameras, NVR/DVR, RTSP/ONVIF, video codecs and bandwidth/storage calculations
• Bash and/or Python scripting experience for automation and troubleshooting
• Excellent problem-solving and communication skills with willingness to travel to customer sites approximately 30–50%

What you’ll learn here

• How AI-powered video analytics solutions are deployed across real customer environments
• How edge devices, GPU servers, cameras, NVRs and VMS platforms are integrated into production systems
• How large multi-site deployments are automated, monitored and maintained
• How video analytics configurations are tuned for different customer site conditions
• How deployment, networking and configuration issues are diagnosed in real-world surveillance environments
• Work on India's first STQC-certified, Made-in-India surveillance platform deployed at national scale
• Deploy AI that runs in the real world on live camera streams and at customer sites
• Gain exposure to hardware, firmware, software, AI and infrastructure under one roof

Ready to take AI from software to the real world?