Deputy Director - AI Solution and Platforms Observability

Overview

Overview:
Senior hands-on individual contributor responsible for enabling enterprise Vision Intelligence capabilities across Computer Vision, Vision-Language Models (VLMs), Vision Agents, Edge AI and IoT. Partners with Domain and Enterprise Architecture teams to translate business needs and architecture patterns into scalable, production-ready capabilities.

Responsibilities

Key Responsibilities:

• Serve as the technicalSME for Vision Intelligence, covering CV, VLMs, Vision Agents, Edge AI and IoT.
• Design, train, evaluate and productionize CV models for detection, classification, segmentation, tracking, OCR, anomaly detection and activity recognition.
• Develop VLM and multimodal solutionsfor image/video understanding, visual reasoning and operational intelligence.
• Build Vision Agentscombining visual intelligence, IoT telemetry, enterprise context, tools and workflows.
• Enable reusable platform capabilities including inference services, APIs, SDKs, model pipelines and reference implementations.
• Deploy and optimize AI workloads across edge GPUs, industrial PCs, smart cameras and cloud/edge environments.
• Integrate cameras, sensors and IoT/OT systems using RTSP, ONVIF, MQTT, OPC UAand related technologies.
• Establish Vision MLOpspractices for datasets, evaluation, CI/CD, deployment, monitoring and model drift.
• Partner with Manufacturing, Warehouse, Quality, EHS and other domains to move solutions from POC Pilot Production Scale.
• Evaluate emerging CV, VLM, Edge AI, Vision Agent and Physical AItechnologies through hands-on prototyping and benchmarking.
• Collaborate with Domain and Enterprise Architectsand mentor engineering teams on Vision Intelligence implementation.

Qualifications

Qualifications:

• Overall 10+ years of overall experience is required.
• Bachelors degree in Computer Science, Engineering, or related field (or equivalent experience)
• 812+ yearsof AI/software engineering experience, including 5+ years in Computer Vision/Vision AI.
• Strong hands-on experience developing and deploying production-grade CV models and real-time video analytics.
• Practical experience with VLMs, multimodal AI and Vision Agents.
• Experience with PyTorch, OpenCV, YOLO, ONNX, TensorRT, NVIDIA DeepStreamor equivalent technologies.
• Experience deploying AI on GPU/edge platforms, containers and Kubernetes/K3s.
• Strong IoT/OT integrationexperience with cameras, sensors, gateways and industrial environments.
• Experience with CV/Vision MLOps, model optimization, evaluation and production monitoring.
• Demonstrated experience taking Vision AI solutions from prototype through production at multiple sites.
• Manufacturing, warehouse, supply-chain, quality, EHS, robotics or industrial automation experience is highly desirable.
• Exposure to Digital Twins, sensor fusion, robotics and Physical AIis a plus.