Principal AI Software Architecture Engineer (f/m/d)

Job Title

Principal AI Software Architecture Engineer (f/m/d)

Role Summary

Lead the technical direction for AI software platforms and deployment technologies for embedded and edge products. The role spans architecture, model translation, compiler/runtime integration, and hardware/software co-design across heterogeneous compute.

Work with hardware, software, product and customer-facing teams to define executable technical roadmaps and production-grade AI deployment solutions for constrained environments.

Experience Level

Senior - Principal-level role. Target profile expects 15+ years preferred; minimum 10+ years in complex software systems or related domains and 5+ years of demonstrated technical leadership or architecture ownership.

Responsibilities

Technical leadership and hands-on architecture ownership across AI toolchains, runtimes and deployment layers for embedded/edge platforms.

• Define and drive long-term architecture strategy for model translation, compilers, runtimes and deployment stacks.
• Lead architecture decisions for heterogeneous deployments across CPU, MCU, MPU, NPU, DSP, GPU and accelerators.
• Guide evolution and integration with compiler ecosystems (e.g., LLVM/MLIR) and related toolchains.
• Drive hardware/software co-design to influence future accelerator and platform capabilities.
• Translate platform needs into technical roadmaps with product, hardware and application teams.
• Mentor senior engineers and technical leads; shape architecture practices across distributed teams.
• Represent technical direction in architecture reviews, customer workshops, partner meetings and executive reviews.
• Support global collaboration and travel (up to 30%) for reviews, workshops and partner engagements.

Requirements

Core technical skills and demonstrated architecture leadership required. Education requirements are summarized separately below.

• Must-have: Proven large-scale software architecture experience and platform evolution for AI deployment.
• Must-have: Deep experience with AI model deployment workflows, toolchains, and runtime integration.
• Must-have: Strong compiler ecosystem knowledge (examples: LLVM, MLIR, IREE, XLA, TVM, OpenXLA) and performance engineering skills.
• Must-have: Programming expertise in C++ and Python; experience with AI frameworks and formats (PyTorch, TensorFlow, ONNX, TFLite).
• Must-have: Experience with embedded/edge constraints (memory, power, latency) and heterogeneous hardware architectures.
• Must-have: Demonstrated technical leadership, cross-team influence and experience in globally distributed engineering organizations.
• Nice-to-have: Contributions to open-source compiler/runtime projects, patents or publications.
• Nice-to-have: Prior experience defining multi-year technical roadmaps and customer-facing strategic leadership.
• Language: Fluent English required; additional languages (German, Japanese, French) are beneficial.

Education Requirements

Master's degree or PhD in Computer Science, Computer Engineering, Electrical Engineering or a related technical field. Equivalent depth of technical achievement and substantial industry experience may be considered.

About the Company

Company: Renesas

Headquarters: Hitachinaka, Japan

Renesas is a global leader in embedded semiconductor solutions, providing high-quality products across automotive, industrial, infrastructure, and IoT sectors. With over 22,000 employees in more than 30 countries, the company focuses on scalable solutions that enhance user experience and drive innovation while committed to sustainability and energy efficiency.