Job description

ABOUT LVT LVT lvt.com 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 lvt.com, 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 lvt.com 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 Manager, Software Engineering 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. ROLE RESPONSIBILITIES - 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. OUR IDEAL CANDIDATE - 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 including model deployment pipelines, evaluation frameworks, observability, and inference optimization. - Physical AI Passion: Strong interest in AI applications involving real-world systems including sensors, video, robotics, IoT, computer vision, or edge intelligence. - Talent Builder: Demonstrated success hiring, mentoring, retaining, and developing high-performing engineering organizations. - Strategic Thinking: Ability to make thoughtful, data-driven decisions and balance long-term platform investments with immediate business needs. - Education: Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field. PREFERRED QUALIFICATIONS - 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. COMPENSATION The beginning annual salary range for this role is $250,200.00 - $300,00.00 USD and is determined by location, job-related experience, and education/training. Total compensation includes annual performance incentives and participation in LVT's equity program. BENEFITS We believe you do your best work when your whole life is supported. We invest in our crew’s health, families, and financial futures with a benefits package designed to support you inside and outside the office. Full-time benefits include, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits (401k match up to 4%), and flexible PTO. LVT IS PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. All candidates must pass a drug screening and background check upon employment. Some roles may also require passing a federal background check and fingerprinting. Must be authorized to work in the U.S. If reasonable accommodation is needed to participate in the job application or interview process, and/or to perform essential job functions, please reach out to your recruiter.

Requirements

Must-haves

We are seeking a Senior Manager, Software Engineering to lead a high-performing engineering team building the next generation of Agentic AI and intelligent distributed systems at LVT.
You should be equally comfortable discussing AI model architectures, distributed system design, inference pipelines, and organizational leadership.
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.
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 including model deployment pipelines, evaluation frameworks, observability, and inference optimization.
Physical AI Passion: Strong interest in AI applications involving real-world systems including sensors, video, robotics, IoT, computer vision, or edge intelligence.
Talent Builder: Demonstrated success hiring, mentoring, retaining, and developing high-performing engineering organizations.
Strategic Thinking: Ability to make thoughtful, data-driven decisions and balance long-term platform investments with immediate business needs.

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningawskubernetespythongojava

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto