• Lead the evaluation, selection, and deployment of a centralized deployment management system
• Design and implement automated deployment pipelines for vessel-based installations
• Create and optimize automated workflows for customer onboarding and provisioning
• Build automation tools and scripts to reduce manual deployment effort to
• Lead and support hardware certification, testing, and validation rocesses in lab environments to ensure optimal performance and compatibility before customer deployment
• Conduct performance benchmarking and cost/performance analysis for hardware selection, guaranteeing efficient and budget-conscious infrastructure choices
• Manage and document product lifecycles, including End-of-Service (EoS), End-of-Life (EoL) planning, and establishing seamless replacement strategies for customer assets

Qualifications

• Minimum 5+ years of relevant experience in system engineering, deployment, or computer vision roles.
• Specific experience in hybrid SaaS and on-prem computer vision systems deployment preferred.
• Proven experience with deployment automation, lifecycle management, and hardware lab maintenance.
• Industry experience in AI, machine vision, robotics, autonomous systems, or related technology sectors is valuable
• Strong, verifiable proficiency in Python for complex orchestration, model/pipeline scripting, and data processing
• knowledge of Bash/Shell scripting for system configuration and administrative tasks

Hands-on experience in administering, configuring, and deploying solutions on both Linux (various distributions) and Windows operating systems

• Orchestration: Experience deploying and managing applications within Kubernetes or similar container orchestration platforms
• Demonstrated ability to understand and design solutions spanning the entire system lifecycle, including hardware, edge devices, NVRs, network components, and cloud services
• Networking & Video: Solid understanding of advanced networking concepts (VLANs, routing, firewalls) and familiarity with video streaming protocols (RTSP, ONVIF) and NVR system optimization
• Performance Analysis: Experience conducting performance benchmarking and complex cost/performance analysis to inform strategic hardware selection decisions
• Asset Management: Practical knowledge and experience in defining and executing product lifecycle management processes (EoS, EoL, asset retirement, and replacement strategies).