Lead Embedded Systems Engineer

Department: Engineering

• Edge Infrastructure Reports To: CTO Type: Full-Time

Panoptyc is an AI-powered retail security and loss prevention platform purpose-built for the micromarket, convenience store, and enterprise retail segments. Our computer vision stack runs at the edge — directly on devices deployed in client environments — to deliver real-time shrink detection, transaction verification, and operational intelligence at scale. We serve enterprise customers and we're growing fast.

This is a high-leverage role at the core of our physical product. The work you do here ships to real hardware in real stores, and the quality of it directly determines the reliability of the platform our customers depend on.

The Role

We're looking for a Lead Embedded Systems Engineer who knows Linux inside and out, loves solving hard problems in the real world, and has a track record of building and shipping things — not just as part of a big team, but on their own. If you have side projects, open source contributions, or personal builds that you can talk about in detail, we want to hear about them.

You'll own the edge device platform end to end — from deployment pipelines and runtime orchestration to remote management and camera integrations in the field. You'll work closely with our ML, backend, and product teams to ensure inference workloads, camera feeds, and device fleets all run reliably in uncontrolled retail environments.

This is not a role for someone who prefers clean lab conditions. It's for someone who gets energized by the complexity of the real world — and who will use every tool available, including LLMs, to move fast and figure things out.

What You'll Own

Edge Device Platform

• Deploy, configure, and maintain edge compute solutions on NVIDIA Jetson and similar embedded Linux platforms
• Own hardware validation for new deployments, balancing compute headroom, thermal constraints, cost, and supply chain reliability
• Architect and maintain systemd service definitions for reliable, observable, auto-recovering edge processes
• Build and manage Docker container orchestration strategies for running CV inference workloads at the edge

• Own our AWS IoT Core integration — device provisioning, shadow state, telemetry pipelines, and fleet-wide configuration
• Build robust OTA update and rollback mechanisms that account for unreliable field connectivity
• Design and maintain remote observability and recovery automation across distributed device fleets

• Integrate with IP camera ecosystems and retail systems in the field
• Ensure video pipeline reliability including reconnection logic, frame integrity checks, and latency-aware buffering

• Work with our computer vision team to ensure inference workloads run reliably on constrained edge hardware
• Profile and optimize memory, thermal, and power envelopes on edge hardware with acceptable duty cycles

• Actively leverage AI coding tools and LLM-assisted workflows as a force multiplier — this is an expectation, not a differentiator
• Document architecture, deployment runbooks, and failure modes rigorously
• Collaborate across engineering, product, and installation/support teams

What We're Looking For

• 5+ years of hands-on experience with embedded Linux systems in production environments
• Comfort with Linux system administration — you know your way around a Linux system deeply, whether that's on a device or a server
• Familiarity with the Yocto Project — you don't need to be an expert, but you can't be someone who looks at it and says "this is too complicated"
• Solid Docker experience including multi-stage builds, resource constraints, and orchestrating multiple services on resource-constrained hardware
• Fluency with Linux systemd — writing unit files, managing dependencies, watchdogs, journald integration, and failure recovery
• Strong programming skills in C, C++, and/or Python — we're not doing advanced metaprogramming, but you need to be comfortable picking up what's needed
• Hands-on experience with NVIDIA Jetson devices in production or serious personal projects
• Proven ability to design for failure: reconnection logic, graceful degradation, remote observability, and recovery automation

• Experience with AWS IoT Core, AWS Greengrass, or similar fleet management tooling for OTA updates and device lifecycle management
• Hands-on experience with RTSP-based camera integration and ONVIF protocol
• Familiarity with SOC 2 environments
• Experience with retail technology ecosystems
• Open source contributions or personal projects related to embedded Linux, OpenEmbedded, or Yocto — show us what you've built

You're the kind of engineer who gets pointed at something new and figures it out. You don't wait for perfect documentation. You've built things on your own — side projects, personal devices, open source contributions — and you can talk about them in detail because you know exactly what you did and why. You're comfortable in small teams where autonomy is real and accountability is high. When something breaks in the field at an inconvenient time, your instinct is to get to root cause, not just restore service.

We're a small, high-output team. If you're a force of nature who loves Linux and wants to put edge AI on your resume, we want to talk.