Senior Product Manager (AI & Analytics)

Join Avigilon, a leader in AI and analytics for physical security. As a Senior Product Manager, you will own the vision, strategy, and execution for key AI and analytics initiatives across the Avigilon platform. You will work with cutting-edge AI technologies and collaborate cross-functionally to ensure seamless delivery.

• Assumer la responsabilité de la vision, de la stratégie et de l'exécution des initiatives clés en matière d'IA et d'analytique au sein de la plateforme Avigilon.
• Collaborer avec les équipes de recherche et d'ingénierie en IA pour évaluer les compromis techniques liés à l'exactitude des modèles, à la latence d'inférence et aux coûts d'infrastructure.
• Diriger une pratique rigoureuse de découverte du marché, mener des entretiens avec les clients et analyser les données d'utilisation pour garantir que les capacités d'IA répondent aux véritables points de douleur opérationnels.

• Production AI/ML Depth: Deep understanding of computer vision, deep learning, LLMs/VLMs, and analytics workflows, with the technical fluency to engage meaningfully with AI researchers on model deployment, optimization, latency trade-offs, and cost-to-serve at scale
• Cross-Functional Influence: Exceptional written, verbal, and relationship skills to present product strategy to senior leadership and align cross-functional engineering, hardware, and marketing teams without direct authority
• Continuous Discovery Practice: Experience running customer discovery, conducting field interviews, and translating qualitative and quantitative insights into product strategy and clear requirements
• Empowered Product Thinking: Exceptional critical thinker who is decisive, possesses both technical and business acumen, and has a proven track record of taking complex AI products from research/discovery through to commercial deployment
• Experience: 5+ years of Product Management experience delivering software, cloud, or enterprise solutions, with a demonstrated track record of shipping AI/ML-driven products or capabilities at production scale (e.g., serving thousands of active users, processing high-volume streaming data, or managing large-scale inference workloads)
• Systems & Scale Thinking: Ability to visualize how edge-to-cloud AI implementations interact at scale, balancing model execution on local hardware versus cloud/on-prem compute costs, bandwidth constraints, and system load
• AI Prototyping: Ability to rapidly stand up AI-generated prototypes to explore possibilities, test hypotheses, and iterate on workflows before engineering build
• Large-Scale GenAI or Agentic AI Deployment: Experience launching or scaling products in production that leverage Vision-Language Models (VLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), or multi-step AI agents
• Security & Computer Vision Domain Knowledge: Prior experience deploying computer vision models or video analytics at scale within physical security, video management systems (VMS), or IoT/hardware environments
• Cloud + On-Prem Hybrid Architecture: Experience scaling products that bridge cloud and on-premise deployments, or managing edge-to-cloud model distribution strategies