Director of Engineering, Applied Intelligence & Data Platforms

LVT•Seattle, WA

1d•$255,000 - $327,000

About The Position

The Director of Engineering, Applied Intelligence & Data Platforms will lead the development of LVT’s core data and intelligence platform, driving the integration of distributed cloud services and applied AI to transform massive sensor data into actionable, real-world insights. We are looking for a leader who balances deep expertise in machine learning with the ability to build and orchestrate & distributed systems at scale. You must have a strong background in the IoT space, with the ability to bridge the gap between high-performance cloud services and edge-computing environments. This leader will oversee multiple existing teams as well as help bootstrap new teams, based on our planned roadmap and customer opportunities - consisting of full-stack developers, MLOps engineers, AI/ML engineers, data scientists, and full stack engineers. You will work closely with existing product and senior leadership to align AI initiatives with LVT business goals and ensure the successful implementation of AI technologies that deliver significant value.

Requirements

Experience: 10+ years of engineering experience, including 5+ years of applied AI/ML leadership.
Cloud & Orchestration: Deep understanding of modern cloud technologies and orchestration engines for high-availability, multi-region services.
IoT Expertise: Proven track record in the IoT space, specifically building infrastructure for cameras and sensors in production environments.
AI Specialization: Working knowledge of computer vision models, Large Language Models (LLMs), and Large Vision Models (LVMs) and Agentic AI frameworks.
Hardware Knowledge: Practical experience deploying and optimizing models for edge hardware (e.g., NVIDIA Jetson).
Technical Skills: Deep understanding of machine learning algorithms, data preprocessing, model evaluation, and deployment. Experience with AI frameworks, concepts and tools like TensorFlow, PyTorch, scikit-learn, LoRA, LLM’s, VLM’s, and CLIP.
Strategic Thinking: Demonstrated ability to think strategically and make data-driven decisions. Experience in developing and executing strategic plans that meet business needs.
Education: Degree in Computer Science, Data Science, Engineering, or a related field.

Responsibilities

Strategic AI Leadership: Work with senior leadership to develop a technical AI strategy that aligns with LVT business goals and strengthens our competitive advantage.
Scalable Architecture: Design and build multi-region distributed services capable of handling massive data throughput from globally deployed IoT sensors and cameras.
Team Management: Mentor and lead a collaborative team of machine learning engineers, MLOps engineers, and data scientists.
Agentic AI & MCP: Lead the architecture and implementation of agentic AI frameworks and define the strategy for LVT’s Model Context Protocol (MCP).
Edge-to-Cloud Integration: Oversee the development of robust data pipelines and infrastructure that span from cloud orchestration engines to edge devices like NVIDIA Jetson.
Model Lifecycle: Establish benchmarks for model performance, monitoring outputs and adjusting for accuracy and product effectiveness.
Data Governance & Ethics: Ensure all AI development adheres to strict data security, privacy, and ethical guidelines within our SaaS environment
Research and Innovation: Stay current with the latest developments in AI research and methodologies. Encourage and support the exploration of new techniques and technologies to enhance the company’s AI capabilities, and strengthen the company’s competitive advantage.
Data Strategy and Governance: Ensure the use of high-quality, reliable data to train AI models. Implement AI data governance best practices to maintain the integrity, privacy, and data security.
Compliance and Ethics: Ensure that AI model development adheres to industry standards, ethical guidelines, and regulatory requirements. Promote responsible AI practices within the organization.
Cross-functional & Stakeholder partnership: Collaborate and Communicate AI strategy, progress, and outcomes to stakeholders, including the executive team, board of directors, and investors.