Senior Software Engineer - Fallback Stack

About Applied Intuition Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co. We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. About the role We are looking for a software architect to own the fallback stack for our L4 trucking program. You will define how the vehicle detects uncertainty, executes minimal risk maneuvers, and set an architecture that scales across trucking and future autonomy programs. At Applied Intuition, you will: Define the architecture for the L4 trucking fallback stack, including interfaces to perception, behavior, planning, control, and the primary autonomy stack. Design strategies for degraded driving, minimal risk maneuvers, and transitions to remote assistance. Specify and review algorithms that detect autonomy degradation and trigger appropriate fallback behaviors or remote intervention. Work closely with behavior, planning, and perception engineers to align safety logic and trajectories with fallback requirements and ODD constraints. Architect and refine interfaces between the vehicle stack and the remote assistance platform for tele-guidance and safe maneuver completion. Provide technical leadership and mentorship as we build the fallback stack team, influencing decisions across trucking and future SDS programs. We're looking for someone who has: Bachelors or Masters degree in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field. 6+ years of experience building autonomy software for L4 autonomous driving systems. Strong programming skills in C++. Experience designing or implementing fallback or degraded driving behaviors in an autonomous driving stack. Hands‑on experience integrating multiple autonomy subsystems into a cohesive system architecture. Nice to have: Experience on L4 trucking or robotaxi programs, especially around degraded driving, fallback behavior, or safety‑critical autonomy. Experience with remote operations, tele‑guidance, or remote assistance systems for autonomous vehicles or robots. Depth in perception, behavior/decision‑making, or motion planning for edge cases, fallback scenarios, or human‑intervention handoffs. Familiarity with automotive safety and autonomy standards (for example, ISO 26262, ISO 21448, UL 4600) or similar frameworks. Experience defining and validating metrics and scenarios for autonomy performance and safety near operational limits. Prior experience helping to build a new autonomy capability or team from scratch. Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full‑time position in the location listed is: $145,000 - $245,000 USD annually. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. #J-18808-Ljbffr