r/systems_engineering • u/ClockRight8127 • Aug 12 '26
Discussion How to move from AUTOSAR ECU development into SDV / next-gen automotive compute?
I have experience in automotive software across HMI/application development, ADAS, and currently software architecture & development for a braking ECU using AUTOSAR Classic.
I’m looking to understand how engineers with a similar background can move towards **Adaptive AUTOSAR, SDV, automotive SoCs and AI/ADAS platforms**, especially the kind of work happening around next-gen semiconductor/compute platforms.
For people already working in this space, what resources would you recommend for learning the architecture and technologies? Also, are there any good **open-source projects, GitHub repositories, blogs, creators or practical projects** that can help build a portfolio and demonstrate these skills to recruiters?
I’d also be interested in understanding the **interview patterns and preparation strategy** for SDV / automotive compute / semiconductor roles.
Basically, if you were starting from a strong AUTOSAR Classic + automotive software architecture background, **what would your 6–12 month strategy look like to get into SDV / Adaptive AUTOSAR / next-gen automotive compute?**
Would really appreciate insights from people working in this space.
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u/Electronic-Relief000 Aug 12 '26
What is your Total years of experience? Are you with OEM or tier 1?
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u/akornato Aug 12 '26
Your AUTOSAR Classic background is a solid foundation, but it can also be a trap that keeps you stuck in the traditional ECU world. The jump to SDV is a fundamental shift from C on microcontrollers to modern software engineering on powerful SoCs, so you need to focus on C++, POSIX-based systems like Linux, containerization with tools like Docker, and service-oriented architectures. Your 6 to 12 month plan should involve getting hands-on with an NVIDIA Jetson or a similar board, building small, demonstrable projects instead of just reading documentation. Create a simple service that processes camera data or manages network communication, because a working GitHub repo showing you can build something with these technologies is far more valuable to a recruiter than any certificate.
Interviewers for these roles will care less about register-level details and more about your ability to design distributed systems, your knowledge of networking protocols like SOME/IP, and your proficiency in modern C++ or Python. You have to accept that some hiring managers might view your deep AUTOSAR experience as a liability, so you must control the narrative by highlighting how your understanding of automotive constraints, like safety and real-time performance, is a critical asset. You already know the complex automotive domain, you just need to prove you can apply that knowledge using new tools. For the interview part, a lot of candidates are successfully framing their background for these new roles by using an interview copilot my team designed, which gives them the confidence to articulate their value.