Principal Engineer-Linux, Middleware & ROS 2 Vehicle Compute Systems

Our client builds embedded software and firmware for the semiconductor and automotive industries, with deep expertise in low-level device software, driver automation, and safety-critical systems. The engineering organization works close to the metal bringing up silicon, developing production firmware, and validating systems to the standards required by modern and autonomous vehicles. The team is increasingly focused on compute, middleware, and networking layers that connect autonomy software to vehicle hardware platforms., We are looking for a Staff / Principal Engineer to architect and lead the Linux platform and middleware layer of a large, complex vehicle compute system the layer where ROS 2, communication middleware, networking, and the operating system come together to carry autonomy and ADAS software reliably onto real hardware. Modern C is the primary language for this role, and you will set the bar for how C is designed, tested, and integrated across the platform. You will think at the level of the whole system: how compute nodes, sensors, networks, and software components interact, where latency and failures come from, and how the platform should evolve as it scales across programs and fleets. You will own the technical roadmap for the platform, set engineering standards that keep it fast and dependable, and provide deep technical oversight across software, hardware, and systems teams. This is a hands-on leadership position. You will remain in the code and on the target for the hardest problems from Linux kernel and scheduler tuning to ROS 2 executor behavior and multi-layer networking while mentoring senior engineers and driving architectural decisions that scale.

What You’ll Do

• Architect and lead the design of the Linux-based vehicle compute platform, ensuring a modular, scalable interface between autonomy/ADAS software and the underlying hardware.
• Own the ROS 2 architecture including node and process layout, executors, and callback groups, QoS policies, launch and lifecycle management, and the DDS layer underneath and set standards for how application teams build on it.
• Set C engineering standards for the platform, including modern C (C 17/20) design, API conventions, code reviews, static analysis, and unit testing with Google Test (gtest) and Google Mock (gmock) as a required part of CI.
• Define the SDK architecture and integration strategy how silicon-vendor SDKs, BSPs, middleware, and internal libraries are wrapped, versioned, and integrated behind clean, testable C APIs that application teams build on.
• Design and optimize the middleware data path for low-latency, high-bandwidth sensor and control data, including DDS vendor selection and tuning, shared-memory / zero-copy transport, and serialization choices.
• Drive Linux platform decisions for real-time and determinism, including kernel configuration, PREEMPT_RT, scheduling policies, CPU isolation, and affinity, cgroups, memory management, and interrupt handling.
• Lead systems engineering for the compute and networking platform, including requirements, interface definitions, end-to-end latency and bandwidth budgets, failure-mode analysis, and traceability from system requirements to software components.
• Architect vehicle and in-platform networking across OSI Layers 1 4 and above, including Ethernet, CAN, UDP/TCP, time synchronization, and how middleware traffic maps onto the network.
• Lead cross-functional integration of new sensors and compute devices into the middleware stack and define standards for data interfaces between teams.
• Drive the technical roadmap for platform health monitoring, diagnostics, and fleet-wide performance optimization.
• Establish engineering standards for Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing, simulation-based validation, and automated performance profiling.
• Provide technical oversight on complex, cross-layer issues spanning application code, ROS 2 and DDS, the Linux kernel, drivers, and the network.
• Mentor senior engineers and raise the technical bar for design, code quality, and system reliability across teams.

• 8 years of software engineering experience, including leading architecture of large, complex systems at the hardware/software interface.
• Automotive industry background, with experience delivering software for vehicle platforms, ECUs, or in-vehicle compute.
• Expert-level modern C (C 14/17/20) as a primary language, with experience building high-performance, thread-safe, memory-efficient Linux systems and strong command of templates, RAII, concurrency, and the standard library.
• Proficiency with unit test frameworks, especially GoogleTest (gtest) and GoogleMock (gmock), including designing testable C code, mocking OS/middleware/hardware dependencies, and running tests in CI.
• Experience with SDK architecture and integration, including designing SDK APIs, integrating third-party and silicon-vendor SDKs into a platform, and managing versioning and ABI/API compatibility.
• Working knowledge of Python for tooling and automation; familiarity with CMake and colcon-based builds.
• Deep Linux systems experience, including kernel and user-space internals, scheduling, memory, IPC, performance profiling (perf, ftrace, eBPF or similar), and platform bring-up.
• Hands-on production experience with ROS 2 and DDS-based middleware, including QoS, discovery, and performance tuning.
• Strong networking background across the stack, including Ethernet, CAN, UDP, TCP, and higher-level protocols such as gRPC, RTP, and HTTP, with the ability to debug at the packet level.
• Systems engineering discipline, including breaking down system requirements, defining interfaces, building latency and resource budgets, and reasoning about failure modes across a large system.
• Ability to understand complex systems end to end and explain them clearly to software, hardware, and program teams.
• Demonstrated cross-functional leadership across software, hardware, and systems teams, with a track record of shipping complex platforms., * Real-world experience with autonomous driving and ADAS systems, including perception, sensor fusion, localization, planning, and control, and an understanding of their platform requirements.
• Experience with autonomy sensors such as lidar, radar, and cameras and their integration into low-latency data pipelines.
• Time-Sensitive Networking, including PTP / gPTP, and Ethernet switching.
• Automotive middleware and frameworks such as SOME/IP, AUTOSAR Adaptive, or zero-copy IPC frameworks such as Eclipse iceoryx.
• Functional safety and process standards such as ISO 26262 and ASPICE.
• Heterogeneous compute performance optimization across CPU, GPU, and accelerators.
• Containerization and orchestration on embedded Linux, along with experience building distributed fleet health-monitoring frameworks.