Summary
✨ AI‑Generated
Join a fast-growing technology team as a Senior Software Engineer and work across backend services, cloud infrastructure, data pipelines, internal tools, and customer-facing software. You will connect edge systems with AI capabilities and operational workflows, taking ownership of meaningful technical projects across a broad engineering surface area.
Highlights
Generalist senior engineering role with broad ownership across backend services, cloud infrastructure, data pipelines, internal tools, and customer-facing experiences, connecting edge systems, AI capabilities, and operations.
Description
About LuminX
Warehouses still run on clipboards and barcode guns.
Every day, billions of dollars in pallets move through loading docks where workers manually scan, count, and verify inventory—and when something goes wrong, no one notices until a customer complains.
LuminX is changing that.
We build AI camera systems that monitor every pallet movement in real time, automatically read labels and barcodes, and surface errors the moment they happen.
We’re already deployed with major customers and growing quickly.
We’ve raised $5.5 million in seed funding from top investors, and our senior team includes alumni from leading robotics and AI companies.
The Role
We’re hiring a generalist software engineer to help build the systems and products that bring LuminX together.
You’ll work across backend services, cloud infrastructure, data pipelines, internal tools, and customer-facing product experiences—connecting our edge devices, AI models, customers, and operations team.
You’ll own meaningful parts of the product from end to end.
One week, you might build an API that processes data from devices in the field; the next, you might ship a customer dashboard, improve a deployment workflow, or design a system for monitoring our growing edge fleet.
You’ll work closely with our robotics and machine learning engineers to turn complex technology into a reliable, usable product.
This is an early-stage startup, so the work is real and the ownership is high.
You’ll ship code to live customer sites, take on systems that don’t yet have a runbook, and make technical decisions that shape how LuminX scales.
If you want to build, ship, and own—not just write specs and hand them off—you’re in the right place.
What You’ll Do
Design and ship backend services and APIs supporting device management, data ingestion, analytics, labeling, permissions, and model orchestration.Build product features end to end, from data models and APIs through internal tools and customer-facing interfaces.Develop data pipelines that move video, inference results, and telemetry between our edge fleet and the cloud.Build and operate the cloud infrastructure powering LuminX using technologies such as AWS, Kubernetes, Terraform, RDS, and S3.Create dashboards and tools that help customers and internal teams understand system performance and take action.Partner with robotics and machine learning engineers to deploy, monitor, and improve systems running at customer sites.Improve the engineering foundations that allow a small team to move quickly, including CI/CD, observability, testing, and incident response.Talk directly with customers and operators to understand problems, iterate quickly, and turn feedback into reliable software.
What We’re Looking For
3+ years of experience building and shipping production software.Strong backend engineering skills and experience designing APIs, data models, and distributed systems.Comfortable moving across backend, infrastructure, and product-facing development.Experience with cloud infrastructure and modern deployment practices.Solid Linux, debugging, and systems fundamentals.Strong product judgment and the ability to turn loosely defined problems into working software.A track record of taking ownership and shipping software that real users depend on.
Bonus Points For
Experience building frontend applications with modern frameworks.Experience managing fleets of edge or IoT devices in production.Streaming or video pipeline experience with tools such as RTSP, GStreamer, Kafka, or Kinesis.Familiarity with MLOps workflows, including model deployment, versioning, and evaluation.Hands-on experience with embedded platforms such as NVIDIA Jetson or Raspberry Pi.Prior experience at an early-stage startup.