Jobs at LVT

Leads UX strategy and design across LVT’s hardware, deployment, web, and mobile product ecosystem. Builds and mentors the design and research organization, establishes scalable design systems, advocates for design at the executive level, and transforms complex technical data into intuitive enterprise experiences. Drives user research, AI-native design workflows, cross-functional collaboration, recruiting, and measurable design outcomes while contributing hands-on to strategic initiatives.

Architect and implement scalable, secure AWS infrastructure supporting AI and IoT systems. Build Terraform-based infrastructure as code, manage Kubernetes clusters, develop GitHub Actions and ArgoCD CI/CD pipelines, engineer cloud-to-field networking, build internal automation tools, and improve observability. Lead technical design reviews, troubleshoot distributed systems, and mentor junior engineers. This is a hybrid role based in Seattle.

Build and operate the cloud backbone for an agentic AI platform, including highly reliable event pipelines, dispatchers, materialized projections, context stores, APIs, and observability. Own scalability, ordering, replay, idempotency, schema enforcement, failure handling, dashboards, alerting, and operational readiness. Partner with edge, data, infrastructure, agent, and computer vision teams to support reliable agent execution across tens of thousands of devices.

Leads product marketing strategy for AI-driven hardware and software products. Develops positioning, executive messaging, pricing and packaging recommendations, sales enablement, competitive intelligence, market research, and go-to-market plans. Partners cross-functionally with Product, Sales, Finance, and Marketing to translate complex technology into customer value, influence product priorities, support major deals, and build scalable marketing processes and collateral.

Designs, scales, secures, and optimizes multi-region AWS infrastructure supporting an AI platform and global IoT edge fleet. Responsibilities include Kubernetes and EKS management, Terraform and Terragrunt infrastructure automation, GitOps deployment pipelines, cloud operations, identity and secrets management, zero-trust security, observability, cost optimization, and technical documentation. The role partners with software and hardware engineering teams to improve system reliability, deployment velocity, and operational health.

Lead software and AI engineering teams building agentic AI platforms, distributed systems, autonomous workflows, and edge-to-cloud intelligence. Responsibilities include technical strategy, scalable architecture, AI model deployment, MLOps, reliability, developer productivity, talent development, and cross-functional execution across cloud, edge, hardware, and product teams.

Own complex, cross-functional technical programs from scoping through launch, translating ambiguous goals into delivery plans, managing dependencies and risks, and providing executive visibility through dashboards and schedules. Partner with engineering, cloud, platform, technology, and ecosystem teams to deliver outcomes. Improve program processes, tools, and reporting while applying AI capabilities to optimize workflows. Experience with developer tools, software pipelines, internal platforms, Jira, Smartsheet, and technical partner delivery is expected.

Own the end-to-end ML and LLM lifecycle, including model packaging, CI/CD, serving, versioning, rollback, monitoring, drift detection, evaluation, guardrails, and cost and latency observability. Define API boundaries between the ML platform and application backend, build self-service deployment tooling, establish operational standards, and mentor engineers. The role supports computer vision, LLM, VLM, and agentic workloads in production.

Own the end-to-end ML data flywheel, including telemetry and video ingestion, layered lakehouse datasets, labeling, annotations, evaluation sets, versioning, governance, provenance, and self-service integrations. Build scalable multimodal data pipelines and libraries for PyTorch, Lightning, and Spark. Establish dataset contracts, quality gates, technical standards, and mentorship while partnering with AI research, MLOps, annotation, edge, and infrastructure teams.

Leads fullstack software engineering teams developing customer-facing web and mobile platforms, scalable backend services, AI-powered workflows, and real-time IoT and video applications. Owns technical strategy, architecture, delivery, engineering excellence, cross-functional alignment, and talent development while partnering with Product, Design, Platform, AI/ML, Security, Infrastructure, and Hardware teams.

Lead backend architecture and technical direction for scalable cloud services and APIs. Build Node.js and TypeScript systems, improve reliability and CI/CD workflows, resolve complex technical issues, and partner cross-functionally on delivery. Mentor engineers, establish development standards, optimize databases and services, and evaluate emerging technologies to support the company’s intelligent site platform.