Senior Director Platform and AI Engineering, Monitoring

Position: Senior Director Platform and AI Engineering, Monitoring (Job ID 3018944)

Summary

The Sr. Director of Platform and AI Engineering, Monitoring, is a strategic leadership role responsible for defining and executing the product vision and roadmap for our AI-driven Monitoring platform and monitoring services. You will be at the forefront of integrating cutting-edge AI and M/L technologies to create new platform's capabilities, ensuring its reliability, scalability, and performance. You will lead a world-class team of engineers, fostering a culture of innovation and excellence within ADT.

This leader will lead high performance team to conceptualize, develop, and launch innovative products and features that leverage AI to provide proactive, intelligent, and personalized security experiences for our customers. This role reports to the VP of Platform Engineering and will be a key member of the product and engineering leadership team.

The Senior Director of Platform & AI Engineering, Monitoring is a key leadership role responsible for architecting, scaling, and optimizing ADT’s next-generation AI-powered monitoring platform. This leader will drive the convergence of AI/ML, real-time IoT orchestration, multimodal data fusion, and human-in-loop operations to deliver reliable, context-aware, and adaptive monitoring at scale.

Duties and Responsibilities

Reporting to the VP of Platform Product and Engineering, this leader will oversee a team of engineers, ML specialists, and platform architects to design and build a resilient, scalable foundation for agentic monitoring — where automation and empathy work together seamlessly. The role spans end-to-end system engineering, AI Ops, AI inference optimization, and cloud-based alarm intelligence, ensuring ADT’s monitoring services are both proactive and predictive.

Build

and Evolve ADT’s AI Monitoring Platform

• Architect and lead the evolution of a cloud-native, microservices-based monitoring platform capable of ingesting billions of IoT events daily across sensors, cameras, and devices.
• Deliver a scalable AI orchestration layer that powers detection, triage, and adaptive response across home, vehicle, and enterprise environments.
• Lead design of a self-learning data fabric that unifies structured, unstructured, and streaming data to enable real-time decisioning.
• Drive infrastructure modernization — including serverless compute, event-driven architectures, and distributed data lakes for low-latency inference.
• Lead the Cross-Device Intelligence Strategy:
  Architect a platform capable of ingesting and synthesizing data from a wide array of IoT devices (beyond just cameras) to create a holistic and contextual understanding of the customer's environment, enabling more predictive and proactive monitoring services.

Deepen AI and ML Engineering Capabilities

• Partner with Data Science leadership to product ionize models for event classification, object detection, behavioral pattern recognition, and anomaly prediction.
• Build robust AI Ops pipelines to automate model deployment, monitoring, retraining, and governance.
• Integrate Generative AI (GenAI) to synthesize monitoring summaries, generate incident context, and power AI-assisted operator experiences.
• Implement reinforcement learning loops where models continuously improve through feedback from human agents and customer outcomes.

Advance Human-in-the-Loop Monitoring Systems

• Design AI workflows that seamlessly integrate human expertise — balancing automation efficiency with empathy and precision.
• Develop AI-assisted incident management tools: event summarization, context retrieval, risk scoring, and next-best-action recommendations.
• Implement real-time feedback loops where operator inputs retrain and optimize AI models for greater situational understanding.
• Define and evolve adaptive escalation protocols that dynamically determine when to route events to human operators versus automated resolution.
• Personalized Monitoring Profiles:
  Develop AI-driven capabilities that allow customers to customize their monitoring preferences, enabling a tailored balance between automated AI responses and human engagement.

Lead Cross-Device and Edge Intelligence

• Drive engineering for edge-AI inference, enabling on-device decisioning…