Embedded Software Engineer (Drone Stack)

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the company creates the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition serves the automotive, defense, trucking, construction, mining, and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. The company is headquartered in Sunnyvale, California, with offices worldwide.

We are an in-office company, expecting full-time employees to primarily work from their Applied Intuition office 5 days a week. Flexibility is recognized, allowing occasional remote work or adjusted schedules to accommodate personal commitments.

About the Role

Applied Intuition is seeking a Software Engineer for the Drone Stack Team to architect and field advanced autonomy and vehicle intelligence systems that bridge hardware and software. In this role, you will bring autonomy stacks to life on real vehicle platforms, stand up integrations, run SIL and HIL evaluations, and support live testing in the field. You will partner with teams across the company to ship dependable, scalable capabilities to both defense and commercial customers.

Responsibilities

• Build and tailor modular, rapidly adaptable autonomy capabilities for a wide range of defense missions, fielding them on embedded Linux and other compute platforms while interfacing with onboard sensors and capturing data.
• Work alongside autonomy engineers to marry autonomy software with vehicle hardware, achieving full integration with aircraft autopilots, datalinks, sensor payloads, PNT/GPS/INS, and ground control stations.
• Develop service-oriented-architecture software and inter-process messaging frameworks for autonomous UAS.
• Perform system-level bring-up, test, and validation spanning software-in-the-loop (SIL) and hardware-in-the-loop (HIL) evaluation.
• Participate in live flight testing across Group 1–5 unmanned aerial vehicles (UAVs).
• Diagnose and resolve challenging software and integration problems to keep systems performant and dependable.
• Engage directly with DoD warfighter domain experts and partner with third-party UAS vendors to bring Applied's autonomy software onto OEM aircraft hardware.

Requirements

• Bachelor's or Master's degree in Robotics, Computer Science, or a related engineering discipline, plus at least 3 years of hands-on robotics experience spanning hardware, software, and systems integration.
• Proficiency in modern C++ (required), with development experience in Docker, containerized deployments, and Linux distributions such as Ubuntu or RHEL.
• Comfort with everyday tooling like git, GitLab, and Visual Studio Code.
• Hands-on integration of robotics or autonomy products with Pixhawk-family autopilots (ArduPilot and/or PX4).
• Working knowledge of common communication buses and protocols: UART/RS232/RS422/RS485, SPI/QSPI, I2C, and Ethernet.
• Exposure to real-time, edge, and safety-critical computing in SIL, HIL, test, and operational settings.
• Strong communication skills and a customer-first approach to project delivery.
• Ability to travel for on-site integrations and demos (roughly 10–20%).
• U.S. citizenship and eligibility to obtain and hold a U.S. security clearance.

Skills

• Modern C++ standards (C++11/17/20), plus Bash and CMake.
• FAA Part 107 Remote Pilot Certificate (nice to have).
• Familiarity with Agile workflows and CI/CD pipelines.
• Hands-on work with COTS compute hardware like NVIDIA Jetson or Raspberry Pi.
• An active U.S. SECRET clearance (nice to have).

Benefits

• Comprehensive health, dental, vision, life, and disability insurance coverage.
• 401k retirement benefits with employer match.
• Learning and wellness stipends.
• Paid time off.

Pay

Compensation at Applied Intuition includes base salary, equity, and benefits. The pay range for this role is $150K - $225K, reflecting the minimum and maximum intended target base salary for new hires. The actual base salary offered will be influenced by factors such as experience, credentials, educational attainment, skill level requirements, and interview performance.