Autonomy Integration Engineer – Drone Stack (Field & Lab)

Drone.vet; Freeport (FL); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Applied Intuition, Inc. is seeking an Autonomy Integration Engineer for the Drone Stack team to bridge hardware, edge software, and field flight operations between lab and airfield.

Lead bring-up of unmanned systems, deploy edge software, troubleshoot networks, and build tooling for data and validation in a role that blends bench work with real-world flight tests. This position offers office-based work with relocation options to Sunnyvale, CA or Ann Arbor, MI, and a path to a hybrid schedule.

Qualifications

• 5+ years in robotics integration or autonomous flight/test engineering.
• Strong Linux CLI, networking, and container deployments.
• Hands-on wiring, soldering, and electronics diagnostics.
• Proficiency in Python, C++, or shell scripting for automation.

Responsibilities

• Lead system bring-up from benchtop to active flight campaigns.
• Deploy and configure edge software across onboard compute and peripheral hardware.
• Troubleshoot vehicle networks and sensor links in real time.
• Develop Python and C++ scripts for data reduction and validation.
• Fabricate wiring harnesses and perform precision soldering.
• Configure IP routing between flight controllers, companion computers, radios, and ground stations.

Skills

Robotics integration

Linux & Networking

Hardware & Electronics

Scripting & Glue Code

Serial/Vehicle protocols

Leadership

Tools

Docker

Oscilloscope

Multimeter

Soldering tools

Job description

Applied Intuition, Inc. is seeking an Autonomy Integration Engineer for the Drone Stack team to bridge hardware, edge software, and field flight operations between lab and airfield.

Lead bring-up of unmanned systems, deploy edge software, troubleshoot networks, and build tooling for data and validation in a role that blends bench work with real-world flight tests. This position offers office-based work with relocation options to Sunnyvale, CA or Ann Arbor, MI, and a path to a hybrid schedule.