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We are looking for a visionary Senior Technical Manager to build and lead our AI software stack for our next-generation NPU platform.

This is a rare opportunity to own the full software layer - from compiler infrastructure to developer ecosystem - and make a lasting impact on how AI runs on silicon.



What You'll Do;

Build and lead a highly skilled AI software & algorithms engineering team, establishing engineering standards, development processes, and technical direction
Define the end-to-end stack - compiler, runtime, kernel libraries, and SDK - enabling efficient AI deployment on our NPU
Drive AI compiler development using technologies like MLIR, TVM, LLVM or similar infrastructures to translate PyTorch/TensorFlow models into optimized NPU execution
Champion model optimization - quantization, pruning, and hardware-aware techniques for maximum performance and power efficiency on the accelerator.
Runtime, Drivers, and Firmware Integration - scheduling, memory management, and low-level software for AI workloads on-chip
AI Kernel Libraries - Guide the development of highly optimized neural network kernel libraries and performance-critical primitives tailored to the architecture of the NPU.
Developer Ecosystem - Define and deliver the SDK, APIs, and development tools that allow internal teams and external developers to deploy AI models easily on the platform.
Cross-Functional Architecture Collaboration - Work closely with silicon architecture and hardware design teams to ensure optimal hardware-software co-design, providing feedback on architecture, performance bottlenecks, and future ISA requirements.

This is a 100% hands-on role combining critical core coding, architectural leadership, intensive mentorship, and driving an AI-First mindset across the engineering culture. Your goal goes beyond shipping features - it is about building and cultivating a sharp, autonomous, and high-performing engineering team.
What You'll Do
Architecture & Code (Hands-on): Lead end-to-end architecture (Backend & Frontend), take ownership of the stack, databases, and repositories, and write complex core system components.
Product-to-Tech Translation: Deconstruct complex product requirements into clear, precise, and actionable technical breakdowns for developers.
Mentorship & Engineering Excellence: Empower and develop team members, conduct rigorous code reviews, run engineering post-mortems (lessons learned), and build a culture of continuous knowledge sharing.
Agile & Delivery: Drive technical task decomposition, set realistic estimations, and execute stable, predictable sprint deliveries.