Principal Engineer

We are seeking an experienced Automotive AI Software Architect (12-15 years) to lead AI-driven software development for automotive MCU platforms. The role involves defining AI agent architectures, MCP integrations, and AI-assisted engineering workflows while ensuring compliance with ISO 26262, ISO/SAE 21434, ASPICE, AUTOSAR, and MISRA C standards. Responsibilities include developing validation frameworks for AI-generated software, supporting automotive applications such as BMS, motor control, and vehicle networking, and driving quality, functional safety, cybersecurity, and technical leadership across engineering teams. Ideal candidates will have deep expertise in AUTOSAR, automotive ECUs, AI-assisted development, Python automation, HIL testing, functional safety, and automotive cybersecurity.

Your role

Key responsibilities in your new role:

• Define and drive the architecture for AI agent skills, autonomous agents, and tool integrations (including Model Context Protocol (MCP) servers) for automotive MCU platforms. This includes multicore system configuration, safety and security peripherals, low-level driver development, and AUTOSAR MCAL configuration.
• Establish and govern the integration of AI-assisted software development within automotive standards and processes, including ISO 26262, ISO/SAE 21434, and Automotive SPICE (ASPICE). Ensure end-to-end traceability from requirements through implementation and testing, while defining review checkpoints and confidence frameworks for AI-generated outputs.
• Ensure that AI-generated software complies with MISRA C standards and project-specific coding guidelines, successfully passes static analysis checks, and correctly implements functional safety and security mechanisms.
• Define comprehensive evaluation frameworks for AI-generated firmware, including benchmark workloads, automated simulation testing, Hardware-in-the-Loop (HIL) validation, and regression-testing strategies to assess the impact of changes in AI models, toolchains, and SDKs.
• Design and develop AI skills and automation capabilities for automotive applications such as electric motor control, Battery Management Systems (BMS), and vehicle communication networks including CAN FD, LIN, and Automotive Ethernet.
• Establish quality standards and best practices for AI-enabled development, conduct technical reviews of skills and solutions developed by engineering teams, mentor team members, and actively contribute to talent acquisition and team growth.
• Collaborate closely with Product Management, Application Engineering, and customers to gather requirements, align expectations, and clearly communicate the capabilities, limitations, and reliability of AI agents in safety-critical automotive software development environments.

Your profile

Qualifications and skills to help you succeed

• 12-15 years of hands-on embedded software development experience, including at least 8 years in automotive ECU software development and 5+ years in technical leadership or architecture roles.
• Proven experience delivering software for ISO 26262-compliant automotive programs at ASIL-B or higher, including development of safety requirements, implementation of safety mechanisms, and creation of required safety work products.
• Strong expertise in AUTOSAR Classic Platform, particularly MCAL and Basic Software (BSW) configuration, with practical experience operating within ASPICE-assessed development processes.
• Deep understanding of multicore automotive MCU architectures from leading vendors, such as Infineon TriCore™, Arm Cortex-R, and Power Architecture-based platforms, including lockstep processing, memory protection schemes, and Hardware Security Modules (HSMs).
• Hands-on experience implementing automotive cybersecurity solutions aligned with ISO/SAE 21434, including secure boot, secure flashing, and platform security mechanisms.
• Proficiency with industry-standard automotive development and validation tools, including Lauterbach TRACE32, Vector CANoe, TASKING or HighTec compilers, and static analysis tools such as Polyspace and Helix QAC.
• Strong Python programming skills for engineering automation, tooling, and workflow optimization.
• Demonstrated expertise in Generative AI applied to engineering workflows, evidenced by at least two of the following achievements, with at least one successfully led, deployed, and adopted by a broader team:
• Designed and implemented an AI-assisted engineering workflow that measurably improved development efficiency, product quality, or engineering productivity.
• Developed frameworks for evaluating AI-generated code using automated validation, testing strategies, and performance metrics tracked over time.
• Applied AI solutions for requirements analysis, traceability management, automated test generation, or code reviews within structured environments governed by ASPICE or ISO 26262.
• Established risk mitigation approaches for AI-generated software, addressing concerns related to licensing, cybersecurity, functional safety, tool confidence, and compliance.
• Ability to articulate a well-founded perspective on the adoption of AI in safety-critical software development, supported by practical examples and a clear understanding of verification, validation, and documentation requirements.
• Experience with Infineon AURIX™ TC3x/TC4x or TRAVEO™ T2G microcontroller platforms, including low-level driver development and platform-specific software libraries.
• Domain expertise in electric vehicle applications, particularly motor control systems and Battery Management Systems (BMS).
• Hands-on experience with Hardware-in-the-Loop (HIL) validation platforms such as dSPACE, Vector VT System, or Typhoon HIL.
• Familiarity with Model-Based Development (MBD) using MATLAB/Simulink and Embedded Coder.
• Knowledge of automotive regulations and standards, including UN R155, UN R156, and ISO 21448 (Safety of the Intended Functionality - SOTIF).
• Contributions to the automotive software or AI engineering community through technical presentations, publications, conference talks, or open-source projects related to automotive tooling, embedded systems, or AI-assisted development.

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Anand Rawal