Staff Software Engineer

Description

The Role

As a Staff Software Engineer on our ADAS/AV Simulation team, you will be the technical leader and chief architect for complex simulation platforms that validate advanced driver assistance and automated driving features at scale. You will design and evolve simulation architectures that coordinate numerous controllers and models across organizations, ensuring consistent behavior from component-level SIL to vehicle-level validation.

Partnering closely with embedded and infotainment partners, and other simulation and controls teams, you will define the technical vision, integration patterns, and standards that allow diverse controllers, tools, and workflows to interoperate reliably. You will architect cloud-native, service-oriented solutions-APIs, microservices, data pipelines, orchestration, and tooling-that accelerate simulation workflows, enable real-time and non-real-time co-simulation, and support continuous delivery of new capabilities.

This role spans hands-on architecture and coding, cross-domain technical leadership, and strategic influence. Joining our team at the Staff level means driving the long-term roadmap for automated and assisted driving simulation, de-risking future milestones, and raising the technical bar across multiple teams and programs.

What You'll Do

Own and evolve the ADAS/AV simulation architecture

• Define and maintain a cohesive simulation reference architecture that supports multi-controller, multi-ECU, and multi-domain SiL simulations with consideration for computability with other MIL, HIL, and vehicle-level validation environments.
• Design robust integration patterns and contracts (APIs, data schemas, synchronization mechanisms) that allow simulation components owned by and other GM teams to interoperate in a predictable, scalable way.
• Drive architectural decisions for time synchronization, data exchange, and orchestration between different simulators, controllers, and plant models (e.g., vehicle dynamics, perception, planning, actuation).

• Serve as the primary technical interface to partner simulation teams-translating requirements, reconciling constraints, and aligning on common interfaces, data models, and toolchains.
• Facilitate and lead design reviews that span multiple organizations, ensuring simulation architectures satisfy both feature team needs and enterprise-wide simulation strategy.
• Anticipate and proactively resolve integration risks between simulation environments, tool chains, controllers, and cloud services ahead of critical program milestones.

• Design and build systems that support large-scale batch and regression simulation in the cloud
• Define and enforce non-functional requirements for performance, reliability, and observability across simulation services.

• Design architectures that can scale with increasing simulation demands: higher-fidelity models, more controllers, larger scenario sets, and tighter program timelines.
• Drive technical strategies for mixed-fidelity simulation (combining high-fidelity and reduced-order models where appropriate)
• Identify gaps in current platforms that could block future ADAS/AV milestones, and define clear technical roadmaps to close those gaps.

• Lead design and code reviews for critical simulation components, setting high standards for architecture, code quality, and documentation.
• Mentor senior and mid-level engineers, growing their ability to contribute to complex distributed systems and simulation platforms.
• Act as a thought leader in ADAS simulation-sharing patterns, guidelines, and reference implementations that raise the bar across the organization.

• B.Sc. and Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related engineering discipline with substantial software experience.
• 10+ years of professional simulation experience, with substantial experience in designing and delivering large-scale, distributed software systems.
• Demonstrated expertise in C++ and/or Python applied to performance-sensitive or systems-level software.
• Demonstrated experience designing and integrating complex systems and systems-of-systems, preferably in simulation, embedded, or controls-heavy domains.
• Experience working within or adjacent to simulation environments (e.g., SIL/HIL platforms, model-based development, or vehicle dynamics/perception/planning simulation).
• Strong background in version control systems (Git) and modern CI/CD workflows and tools (e.g., Jenkins, GitHub Actions, Azure DevOps or similar).
• Proficiency with service-oriented and API-centric architectures (REST/gRPC APIs, message buses, asynchronous processing) and designing clear, stable contracts between services.
• Familiarity with automotive communication technologies such as CAN, automotive Ethernet, SOMEIP, UDP as well as logging and replay systems used in ADAS/AV development.
• Excellent communication skills, both oral and written, with the ability to explain complex technical concepts to diverse stakeholders
• Proven ability to manage multiple concurrent efforts, keep work organized and well-documented, and drive initiatives from concept through implementation and adoption.
• 5+ years of experience with Active Safety or Automated Driving simulation in SIL/HIL/MIL/Vehicle-level validation setups and hands on experience with one or more ADAS/AV simulation tools and environments such as CarSim, IPG CarMaker, Carla, Applied Intuition, MSC Vires, dSPACE ASM, or comparable platforms.

• Experience architecting or operating large-scale scenario-based regression simulation pipelines in the cloud.
• Practical experience with containerization (Docker) and container orchestration platforms (Kubernetes, ECS, or similar) in production or large-scale environments
• Experience designing and integrating cloud-native data pipelines for simulation results (e.g., ingestion, storage, indexing, and analytics for large volumes of simulation outputs).
• Practical knowledge of synchronization and co-simulation techniques (e.g., time-step coordination, real-time vs non-real-time simulation, coupling different simulators/controllers).
• Experience applying Systems Engineering principles to complex, safety-critical systems: requirements management, traceability, interface definition, and verification and validation strategies.
• Understanding of how simulation artifacts support safety cases, validation evidence, and regulatory/compliance needs for ADAS/AV features.