Director

1. AI Product Strategy & Execution
Define and drive the product vision, roadmap, and execution strategy for AI-powered solutions, with a focus on computer vision technologies and real-time AI models.Own key product KPIs, including model accuracy, latency, adoption rate, and computational efficiency for cloud/edge deployments.Lead the end-to-end product lifecycle, from conceptualization and prototyping to large-scale deployment.Ensure scalability, modularity, and reusability of AI & Engineering components across different use cases, by working closely with Engineering and AI scientist team .Optimize AI model performance for edge devices, low-latency processing, and cloud-scale inference.Establish robust processes for development, QA testing, and deployments within the team.2. Product Engineering for Cloud and Edge deploymentsAI Product Engineering & Scalable ArchitectureArchitect and optimize scalable AI/ML pipelines, ensuring low-latency, high-availability systems.Collaborate with AI/ML teams to integrate Computer Vision, Deep Learning, and Reinforcement Learning models into production systems.Cloud Engineering & Infrastructure Design and implement highly scalable, distributed cloud infrastructure on Cloud (AWS, Azure, or GCP)Implement containerization (Docker, Kubernetes) and microservices architecture for AI-driven applicationsEdge Deployment & Optimization AI model deployment on edge devices, ensuring efficiency in resource-constrained environments.

3. AI Solutioning & Technical Problem-Solving
Partner with AI and engineering teams to define, train, and deploy computer vision models for real-time applications.Guide experimentation and model fine-tuning to improve object detection, tracking, segmentation, and classification tasks.Drive decisions on model architectures (CNNs, Vision Transformers, YOLO,Reinforcement learning etc.) and deployment strategies for cloud (AWS/GCP/Azure) and edge (NVIDIA Jetson, TPUs).Work with data science teams to ensure high-quality labeled datasets, model explainability, and model stability.Optimize AI pipelines for real-time inferencing, multi-camera vision processing, and computational efficiency.Balance experimentation and rapid delivery, ensuring faster time-to-market for AI innovations.

Technical Acumen: Strong understanding of computer vision models (CNNs, Vision Transformers, YOLO, TrackNet, etc.), data pipelines, and AI/ML deployment architectures
Cloud & Edge AI Deployment: Experience in deploying AI models on cloud (AWS/GCP/Azure) and edge (Jetson, FPGAs, TPUs) environments, optimizing for latency and efficiency.Strategic Thinking & Solutioning: Ability to define AI-driven solutions for complex, open-ended problems.

Stakeholder & CXO Influence: Proven ability to engage and influence senior executives, business leaders, and technical teams.Agile Product Development: Experience with JIRA, Scrum, backlog grooming, and iterative development.Excellent Communication: Ability to articulate technical AI concepts to both technical and non-technical audiences.

Experience in AI Product Management: 13-16 years in product management, with a strong track record in AI/ML-powered solutions, real-time data products, or high-tech innovations.