Senior Engineering Manager, Agentic AI Platforms

LVTSeattle, WA
$250,200 - $302,900

About The Position

LVT is redefining how businesses operate in the physical world, moving beyond traditional security solutions to deliver AI-driven, actionable intelligence that makes sites smarter, safer, and more secure. Since pioneering our first mobile, solar-powered units, our commitment to scrappy, hands-on innovation has made us an established leader and one of the fastest-growing companies in intelligent site technology. We are building the next generation of solutions—from our physical units in the field to a powerful Agentic AI platform—that allows our customers to gain unprecedented visibility and control over safety, compliance, and operations. This is your chance to join a cutting-edge team that isn't just watching the world change, but actively building the technology that is changing it. We’re a team that’s focused on growth and innovation, and we’re proud that our crew, products, and leadership are being recognized for it. A Top-Tier Growth Company: Named one of the Financial Times’ Fastest Growing Companies 2025 and #10 on the Inc. 5000 Rocky Mountain Regional list for 2025. Innovative Leadership: Our CEO, Ryan Porter, was named an EY Entrepreneur of the Year 2025, and our CTO, Steve Lindsey, was inducted into the Silicon Slopes CTO Hall of Fame in 2024. Product & Software Excellence: We were named one of The Software Report’s Top 100 Software Companies of 2023 and are a winner of the Security Today Govies Award for 2025. 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.

Requirements

  • 10+ years of software engineering experience including 4+ years managing and growing engineering teams in high-growth environments.
  • Experience building and deploying AI-driven systems utilizing machine learning models, LLMs, multimodal AI, recommendation systems, or agentic architectures.
  • Experience designing systems involving AI agents, memory systems, orchestration frameworks, MCP architectures, retrieval systems, or autonomous workflows.
  • Strong experience designing highly scalable distributed systems and cloud-native services supporting tens of thousands of edge devices and millions of events per day.
  • Strong background with cloud platforms such as AWS and modern container orchestration technologies including Kubernetes.
  • Strong experience in languages such as Python, Go, C++, or Java and experience building APIs and large-scale backend systems.
  • Familiarity with ML infrastructure and tooling including model deployment pipelines, evaluation frameworks, observability, and inference optimization.
  • Strong interest in AI applications involving real-world systems including sensors, video, robotics, IoT, computer vision, or edge intelligence.
  • Demonstrated success hiring, mentoring, retaining, and developing high-performing engineering organizations.
  • Ability to make thoughtful, data-driven decisions and balance long-term platform investments with immediate business needs.
  • Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.

Nice To Haves

  • Experience with Computer Vision, Large Vision Models, or multimodal systems.
  • Experience deploying AI models to edge environments including NVIDIA Jetson or similar hardware.
  • Experience with AI frameworks and tooling including TensorFlow, PyTorch, LangGraph, MCP frameworks, vector databases, and inference platforms.
  • Experience with AI safety, guardrails, evaluation frameworks, and memory systems.

Responsibilities

  • 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.
  • 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.
  • 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.
  • Partner with AI/ML teams on training, deployment, evaluation, and operationalization of models including LLMs, VLMs, and multimodal systems.
  • Drive architecture that spans cloud services and edge infrastructure, ensuring intelligent orchestration across cameras, sensors, and distributed compute environments.
  • Translate product strategy into technical roadmaps and execution plans while balancing innovation, reliability, scalability, and delivery commitments.
  • Establish strong engineering practices around architecture reviews, operational excellence, reliability, observability, AI evaluation frameworks, and development workflows.
  • Drive adoption of AI-assisted development practices and tools to improve engineering velocity and increase team leverage.
  • Partner closely with Product, Hardware, Security, Infrastructure, and Architecture organizations to align priorities and accelerate delivery.
  • Maintain awareness of emerging trends in Agentic AI, AI infrastructure, Physical AI, and distributed computing. Encourage experimentation and thoughtful technology adoption.

Benefits

  • Comprehensive health, dental and vision coverage
  • Retirement benefits (401k match up to 4%)
  • Flexible PTO
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