Senior Engineering Manager, Agentic AI Platforms

About the 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.

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.

Qualifications

• 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.