Senior Manager, Software Engineering - Agentic AI Platforms

LiveView Technologies•Seattle, WA

9h•$250,200 - $300,000

About The Position

LVT is seeking a Senior Manager, Software Engineering to lead a high-performing team building Agentic AI and intelligent distributed systems. The role is at the center of Physical AI innovation, connecting cloud intelligence with edge devices operating in real-world environments. The manager will work closely with Product, Architecture, AI/ML, Edge, and Platform teams to turn large streams of sensor and video data into actionable intelligence, while attracting, mentoring, and retaining engineering talent. The position leads development of AI-driven services, autonomous workflows, distributed systems, and platforms. It calls for a leader able to engage with AI model architectures, distributed-system design, inference pipelines, and organizational leadership. The role also translates product strategy into technical roadmaps and execution plans, balancing innovation, reliability, scalability, and delivery commitments. LVT describes itself as a fast-growing intelligent site technology company building solutions spanning physical field units and an Agentic AI platform. The annual salary range begins at $250,200 and extends to $300,000 USD, with the posting noting that compensation depends on location, job-related experience, and education/training. Total compensation includes annual performance incentives and participation in the company’s equity program. Full-time benefits include comprehensive health, dental, and vision coverage, retirement benefits with a 401(k) match up to 4%, and flexible PTO. Candidates must be authorized to work in the U.S. and pass a drug screening and background check upon employment; some roles may also require a federal background check and fingerprinting.

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 using 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 with 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 such as 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 a related field.
Must be authorized to work in the U.S.; candidates must pass a drug screening and background check upon employment. Some roles may require a federal background check and fingerprinting.

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 and AI engineers; recruit talent and foster mentorship, ownership, and retention.
Lead development of Agentic AI systems using AI agents, memory systems, orchestration frameworks, and autonomous workflows for intelligent decision-making and real-world automation.
Partner with Principal Engineers and Architects to design and build resilient, highly available distributed services for 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 spanning cloud services and edge infrastructure, coordinating intelligence across cameras, sensors, and distributed compute environments.
Translate product strategy into technical roadmaps and execution plans, balancing innovation, reliability, scalability, and delivery commitments.
Establish engineering practices for 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 team leverage.
Partner with Product, Hardware, Security, Infrastructure, and Architecture organizations to align priorities and accelerate delivery.
Track emerging trends in Agentic AI, AI infrastructure, Physical AI, and distributed computing, and encourage experimentation and thoughtful technology adoption.