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Software Engineer & System Architect

Iman has strong software engineering skills built on over 20 years of coding experience, with a deep foundation in digital signal processing and applied mathematics. He is experienced in object-oriented programming and applying design patterns to build scalable, maintainable systems end-to-end, from frontend interfaces to cloud-based backend architectures. He consistently translates complex problems into practical, high-performance solutions, with a focus on clean code, solid system design, and real-time data processing. He combines deep technical expertise with strong product thinking, including meticulous attention to user workflows through continuous user testing and iteration, enabling rapid prototyping and delivery of impactful software solutions. Here are a few examples of recent projects.

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Scriptover

Healthcare AI Platform Scriptover Technologies Inc., California Product Manager & Full-Stack Developer May 2025 - Present

An AI-driven veterinary platform that streamlines clinical workflows and reduces documentation time. It generates structured clinical insights from multimodal inputs—including conversations, medical images, lab data, and patient history—saving veterinarians up to 3 hours per day and reducing staff costs by 40%. The system supports AI-assisted intake, SOAP note generation, dental charting, and real-time collaboration across devices using WebSockets with server-side state management for consistency. Designed with veterinarians, it transforms paper-based workflows into scalable digital systems. Built on a scalable AWS architecture, it supports enterprise deployments and achieved 83% accuracy on NAVLE benchmarks.

Veterinary clinics rely on fragmented, paper-based or partially digitized workflows, leading to slow documentation, inconsistent records, and limited scalability. The challenge was to unify these workflows into a single system while ensuring reliable multimodal data processing, real-time collaboration, and accurate AI-generated outputs grounded in patient-specific data.

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