Senior Engineering Manager, Agentic AI Platforms

Senior Engineering Manager, Agentic AI Platforms

Seattle, Washington, United States

ABOUT THIS ROLE

We are seeking a Senior Engineering Manager to lead a high-performing engineering team building the next generation of Agentic AI and intelligent distributed systems at LVT.

This role sits at the center of Physical AI innovation and requires a leader who combines strong engineering fundamentals with deep passion for emerging AI technologies. You will lead teams building AI-driven services, autonomous workflows, distributed systems, and platforms that connect cloud intelligence with edge devices operating in real-world environments.

You will work closely with Product, Architecture, AI/ML, Edge, and Platform teams to transform large-scale streams of sensor and video data into actionable intelligence. This role requires someone who can build scalable systems while attracting, mentoring, and retaining exceptional engineering talent.

You should be equally comfortable discussing AI model architectures, distributed system design, inference pipelines, and organizational leadership.

• Team Leadership & Talent Development:
  Lead, coach, and grow a high-performing team of software engineers and AI engineers. Recruit exceptional talent while building an environment that promotes mentorship, ownership, and long-term retention.
• Agentic AI Platforms:
  Lead the development of systems that leverage AI agents, memory systems, orchestration frameworks, and autonomous workflows to enable intelligent decision-making and real-world automation.
• Scalable Distributed Architecture:
  Partner with Principal Engineers and Architects to design and build resilient, highly available distributed services capable of supporting large-scale deployments and high-throughput workloads.
• AI & Machine Learning Systems:
  Partner with AI/ML teams on training, deployment, evaluation, and operationalization of models including LLMs, VLMs, and multimodal systems.
• Edge-to-Cloud Intelligence:
  Drive architecture that spans cloud services and edge infrastructure, ensuring intelligent orchestration across cameras, sensors, and distributed compute environments.
• Technical Strategy & Execution:
  Translate product strategy into technical roadmaps and execution plans while balancing innovation, reliability, scalability, and delivery commitments.
• Engineering Excellence:
  Establish strong engineering practices around architecture reviews, operational excellence, reliability, observability, AI evaluation frameworks, and development workflows.
• AI Productivity & Developer
  
  Experience:
  
  Drive adoption of AI-assisted development practices and tools to improve engineering velocity and increase team leverage.
• Cross-functional Leadership:
  Partner closely with Product, Hardware, Security, Infrastructure, and Architecture organizations to align priorities and accelerate delivery.
• Innovation Leadership:
  Maintain awareness of emerging trends in Agentic AI, AI infrastructure, Physical AI, and distributed computing. Encourage experimentation and thoughtful technology adoption.

• Engineering Leadership
  
  Experience:
  
  10+ years of software engineering experience including 4+ years managing and growing engineering teams in high-growth environments.
• AI Systems
  
  Experience:
  
  Experience building and deploying AI-driven systems utilizing machine learning models, LLMs, multimodal AI, recommendation systems, or agentic architectures.
• Agentic AI Expertise:
  Experience designing systems involving AI agents, memory systems, orchestration frameworks, MCP architectures, retrieval systems, or autonomous workflows.
• Distributed Systems Expertise:
  Strong experience designing highly scalable distributed systems and cloud-native services supporting tens of thousands of edge devices and millions of events per day.
• Cloud & Infrastructure
  
  Experience:
  
  Strong background with cloud platforms such as AWS and modern container orchestration technologies including Kubernetes.
• Technical Foundation:
  Strong experience in languages such as Python, Go, C++, or Java and experience building APIs and large-scale backend systems.
• MLOps & AI Infrastructure:
  Familiarity with ML infrastructure and tooling…