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
LVT is building an agentic AI platform that enables autonomous agents that perceive real-world environments, reason over them, and act. Agents operate on an event pipeline that feeds them what's happening across tens of thousands of edge devices and carries their decisions back out to the field. This role builds and hardens the cloud backbone of that platform the event pipeline agents consume from and act through, and the context stores they query.
You'll own the cloud-side reliability, throughput, and scale of the event pipeline, the router/dispatcher that fans events to intelligence services, the projections that make events queryable (including the agent-facing, MCP-exposed context layer), and the observability that keeps it healthy under load.
You will build the platform that lets agents run reliably at fleet scale. You'll partner closely with the edge team that produces events, the data team that owns the lakehouse you feed, infrastructure/operations who run the managed log and broker, and the engineers building the agent and CV workflows that consume your platform.
ROLE RESPONSIBILITIES
- Harden the event pipeline: Make the cloud pipeline production-grade consumer reliability, delivery and ordering guarantees, replay, idempotency, dead-letter handling, and schema/contract enforcement at the boundary.
- Serve the agent layer: Make the dispatch path to agent and CV workflows reliable, and expose the event projections via MCP / agent-facing query interfaces that agents read for context, so the agentic platform has a dependable substrate to run on.
- Scale ingress and projections: Stand up and scale the materialized stores the pipeline serves from (operational hot store, cold capture into the lakehouse), keeping each projection fit to its access pattern and rebuildable from the log.
- Observability and operability: Own the signals that make the pipeline supportable, own dashboards, alerting, and feature flags.
OUR IDEAL CANDIDATE
- Backend / Distributed Systems Depth: 6+ years building and operating backend or distributed systems in production at scale, with strong systems and API design experience.
- Event Streaming / Log-Based Architecture: Hands-on with Kafka or a comparable log/streaming system; topic and partition design, consumer-group semantics, delivery guarantees, replay, and schema-registry integration.
- Reliability & Observability: A track record of hardening services for production including SLOs, metrics and alerting, dead-letter and failure handling, and the operational maturity to own on-call trade-offs.
- Storage & Projection Patterns: Comfortable choosing and operating different stores per access pattern (document/relational hot stores; object storage / lakehouse for cold and analytical).
- Technical Foundation: Strong in Go and/or Python; experience building APIs and large-scale backend services.
- Cloud-Native: AWS and Kubernetes, with a bias toward open, cloud-portable components.
- Education: Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent practical experience.
PREFERRED QUALIFICATIONS
- Building agent-facing or MCP data-access layers, governed query interfaces over operational data for autonomous consumers.
- Integrating agent or CV runtimes onto an event pipeline as pluggable consumers.
- Stream-processing frameworks (Benthos/Bento, Flink, or similar).
- Schema and contract tooling (protobuf/Avro, schema registry).
- Lakehouse producer experience (Iceberg / S3, CDC); MQTT / IoT ingest at scale (EMQX or comparable).
COMPENSATION
The beginning annual salary range for this role is $185,000 - $230,000 USD and is determined by location, job-related experience, and education/training. Your total earning potential is amplified by a bonus structure tied to meeting goals, and you will become an owner from day one through our employee 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
Harden the event pipeline: Make the cloud pipeline production-grade consumer reliability, delivery and ordering guarantees, replay, idempotency, dead-letter handling, and schema/contract enforcement at the boundary.
Observability and operability: Own the signals that make the pipeline supportable, own dashboards, alerting, and feature flags.
Backend / Distributed Systems Depth: 6+ years building and operating backend or distributed systems in production at scale, with strong systems and API design experience.
Event Streaming / Log-Based Architecture: Hands-on with Kafka or a comparable log/streaming system; topic and partition design, consumer-group semantics, delivery guarantees, replay, and schema-registry integration.
Reliability & Observability: A track record of hardening services for production including SLOs, metrics and alerting, dead-letter and failure handling, and the operational maturity to own on-call trade-offs.
Storage & Projection Patterns: Comfortable choosing and operating different stores per access pattern (document/relational hot stores; object storage / lakehouse for cold and analytical).
Technical Foundation: Strong in Go and/or Python; experience building APIs and large-scale backend services.
Cloud-Native: AWS and Kubernetes, with a bias toward open, cloud-portable components.
Education: Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice-to-haves
Building agent-facing or MCP data-access layers, governed query interfaces over operational data for autonomous consumers.
Integrating agent or CV runtimes onto an event pipeline as pluggable consumers.
Stream-processing frameworks (Benthos/Bento, Flink, or similar).
Schema and contract tooling (protobuf/Avro, schema registry).
Lakehouse producer experience (Iceberg / S3, CDC); MQTT / IoT ingest at scale (EMQX or comparable).
Application prep
Use the role’s language and application details while tailoring your materials.