Product Manager, Staff - AI Video Surveillance

Job description

**Company:** Qualcomm India Private Limited **Job Area:** Engineering Group, Engineering Group > Software Engineering **General Summary:** We are seeking a highly skilled Product Manager Staff AI Video Surveillance to lead the strategy, development, and delivery of AI-powered video analytics and surveillance solutions. This role sits at the intersection of AI/ML, edge computing, and video surveillance systems, driving the end-to-end product lifecycle from concept to deployment. You will work closely with customers and internal stakeholders to gather and refine product requirements and translate them into scalable, high-impact solutions. - Engage with customers and internal stakeholders to gather detailed product requirements and use cases - Continuously capture and document new requirements emerging from ongoing discussions - Drive requirement clarification sessions to eliminate ambiguities and ensure alignment across engineering, product, and business teams - Translate business needs into clear, structured product requirements and functional specifications for development teams Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc. **Job Responsibilities** Product Strategy & Roadmap - Define and own the product vision, strategy, and roadmap for AI-based video surveillance solutions - Identify high-impact use cases (e.g., intrusion detection, face recognition, behavior analytics) - Align product direction with business goals and market opportunities Customer & Market Understanding - Gather and analyze customer requirements across enterprise, retail, and industrial deployments - Conduct competitive analysis and track trends in AI, video analytics, and edge computing - Translate customer problems into scalable product requirements Product Development & Execution - Collaborate with AI/ML, embedded, and cloud engineering teams to design and build solutions - Define product requirements, specifications, and feature prioritization - Drive the end-to-end product lifecycle from ideation to deployment and iteration Cross-functional Leadership - Act as the bridge between: - Engineering (AI, embedded, cloud) - Business teams (sales, marketing) - External partners and customers - Ensure alignment and timely execution across all stakeholders **Skills & Experience** Technical Skills - Strong understanding of: - AI/ML and Computer Vision (object detection, tracking, classification) - Video streaming protocols (RTSP/RTP/ONVIF) - Edge computing platforms and IoT devices. - Familiarity with cloud platforms and distributed systems Product & Business Skills - Proven experience in product management (end-to-end lifecycle) - Ability to define product strategy, roadmap, and go-to-market plans - Strong analytical and problem-solving skills - Experience with enterprise or industrial solutions is a plus. Education - Bachelors or masters degree in: - Computer Science / Engineering - MBA (preferred but not mandatory). **Preferred Experience** 9-12 years of experience, including: - Experience working on AI-based video surveillance, CCTV, or VMS solutions with real-world deployments. - Experience in building or managing end-to-end video analytics solutions (camera edge cloud VMS/command center) - Exposure to edge AI platforms (e.g., Qualcomm, NVIDIA, or similar embedded systems) and device-side optimization. - Experience with computer vision use cases such as face recognition, object detection, tracking, and behavior analytics. - Understanding of video pipelines including ingestion, decoding, analytics, and event generation. - Experience in large-scale deployments (e.g., smart city, retail, enterprise security, industrial environments).