ADT · 19 hours ago
Senior Director Platform and AI Engineering, Monitoring
8880 Esters Blvd, Irving, TX, 75063, US
Full-time
Onsite
Director/Executive
10+ years expADT is a leading security and monitoring solutions provider, and they are seeking a Senior Director of Platform and AI Engineering, Monitoring. This strategic leadership role involves defining and executing the product vision for AI-driven monitoring platforms, leading a team to innovate and enhance monitoring services through advanced AI and machine learning technologies.
Cyber SecurityHomeland SecurityInformation TechnologySecuritySmart Home
Responsibilities
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
Partner with Data Science leadership to productionize 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
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
Develop AI-driven capabilities that allow customers to customize their monitoring preferences, enabling a tailored balance between automated AI responses and human engagement
Drive engineering for edge-AI inference, enabling on-device decisioning for faster verification and lower bandwidth consumption
Orchestrate cross-device intelligence, unifying camera, audio, motion, and environmental data into a single contextual model
Build resilience into field-deployed systems with federated learning and failover monitoring across diverse connectivity environments
Define platform-wide SLOs/SLIs for latency, uptime, and inference accuracy, ensuring mission-critical reliability
Implement modern observability frameworks across all AI and microservice layers
Build a culture of continuous deployment with zero-downtime upgrades, leveraging Kubernetes, Terraform, and CI/CD automation
Oversee multi-region, fault-tolerant infrastructure across public cloud environments (AWS, GCP, Azure)
Develop a digital twin and simulation environment for large-scale testing of alarm scenarios, sensor events, and agentic responses
Partner with Product and UX to rapidly prototype new monitoring experiences, testing desirability, feasibility, and performance
Establish internal “AI Experience Labs” to test multimodal AI applications — video, audio, voice, and textual incident data — in real environments
Build and mentor a diverse, high-performing team of platform, AI, and MLOps engineers
Cultivate a culture of technical excellence, experimentation, and measurable business impact
Drive alignment across Product, Data Science, and Operations to ensure AI technology translates into real-world value
Design and implement AI models that intelligently triage and prioritize video events, distinguishing between critical and non-critical incidents to optimize human operator response times and efficiency
Develop workflows and interfaces that seamlessly integrate human operators for verification and contextual analysis of AI-generated alerts, ensuring accuracy and reducing false positives
Define and evolve adaptive response protocols where AI handles routine events autonomously, while escalating complex or ambiguous situations to human monitoring professionals for expert intervention
Innovate on tools and features that empower human agents with AI-powered insights, such as summarized event timelines, relevant historical data, and predictive analytics, to enhance their decision-making during incidents
Qualification
Required
10+ years of engineering experience with at least 5+ years leading large, distributed teams delivering production-grade AI or platform systems
Proven expertise in cloud-scale architectures, real-time streaming, and microservices design
Deep understanding of AI/ML systems, including model lifecycle management, MLOps, feature stores, and data governance
Experience integrating GenAI, LLMs, or multimodal AI into customer-facing products
Mastery of modern cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker)
Strong analytical and problem-solving skills with a data-driven approach to decision-making
10+ years of engineering experience with a track record of successfully launching and scaling B2B or B2C products
5+ years of experience in a leadership role, managing and mentoring a team of technical leaders
Deep understanding of containerization and orchestration technologies (Kubernetes, Docker), infrastructure as code (Terraform, CloudFormation), and CI/CD principles and tools
Proven ability to develop and execute a product strategy that drives business growth
Excellent communication, presentation, and interpersonal skills, with the ability to influence and align stakeholders at all levels
Strong analytical and problem-solving skills, with a data-driven approach to decision-making
Bachelor's or master's degree in computer science, AI, or related field (PhD preferred)
Preferred
Preferred background in IoT, computer vision, or event-driven systems
Experience in the security, smart home, or IoT industries is a plus
Company
ADT
ADT is a security company that provides smart home solutions and business security.
1001-5000 employees
H1B Sponsorship
ADT has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (25)
2024 (42)
2023 (34)
2022 (40)
2021 (32)
2020 (20)
Funding
Current Stage
Public CompanyTotal Funding
$4.1BKey Investors
State FarmGoogle
2025-10-28Post Ipo Debt· $325M
2025-09-30Post Ipo Debt· $1B
2025-03-03Post Ipo Secondary
Leadership Team
Jim DeVries
Chairman, President and Chief Executive Officer
Jeff Likosar
President, Corporate Development and Chief Financial Officer
Recent News
2026-01-07
2025-12-24
2025-12-22
Company data provided by crunchbase