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
  
  

Minimum Qualifications

• 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

• Bachelor's or master's 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).
  
  

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