Product Manager - AI SDK / Model-Serving Product Manager - IL

We’re a fast-moving, US-Israeli AI startup building next-generation infrastructure for the world’s most demanding AI workloads. Our mission is to accelerate the future of intelligence and make it ubiquitously accessible by delivering full stack custom AI servers optimized for large-scale inference and training.

Backed by top-tier investors and led by industry veterans, we’re scaling rapidly. We seek forward-thinking engineers and operators who thrive in a collaborative environment and excel at solving complex challenges from first principles. If you want to build infrastructure that fundamentally changes what the world can accomplish with AI, come join us!

About The Position

We are building the next generation of AI infrastructure-from custom silicon to the servers and systems that power the world's largest AI models. Our vertically integrated approach enables us to optimize every layer of the AI compute stack, delivering breakthrough performance, efficiency, and scalability.

We’re looking for an experienced software product manager to define and deliver the software stack that makes our system seamless for developers and cloud infrastructure teams. You’ll own the compiler roadmap, runtime engines, and framework integrations that take standard deep learning model representations and turn them into highly optimized execution paths on the Ignite APU. The goal is simple to state and hard to achieve: customers should be able to bring the models and tools they already use and get excellent inference performance without having to think about the hardware underneath.

Responsibilities

• Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
• Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
• Compiler Pipeline and Toolchain Roadmap: Define requirements for the software and AI model compilation toolchain
• Framework Integration and Interoperability: Lead product partnerships and technical integrations with major machine learning frameworks and runtimes, ensuring native support for PyTorch, JAX, vLLM, SGLang, and Hugging Face Optimum without requiring customer code modifications.
• High-Performance Kernel Optimization Roadmap: Define performance optimization roadmap for low-level operator libraries, including BLAS, custom OpenAI Triton kernels
• Scale-Out and Clustering Orchestration: Define requirements for clustering and multi-node scale-out configurations, ensuring seamless execution across scale-out setups utilizing SLURM, Ray, LMCache, etc.
• Developer Platform Usability: Act as the primary advocate for developer experience, monitoring how software compiles and executes in customer sandboxes, and proactively removing the need for manual memory management scripts, custom compiler hacks, or API wrappers.
  
  

• Education: Master of Science (M.Sc.) or Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics is a strict, non-negotiable requirement.
• AI Software Stack Expertise: Minimum of 5 to 8 years of experience in product management or software systems engineering, with a proven track record of shipping compiler technologies, deep learning frameworks, or developer platform tools.
• Parallel Programming Fluency: Deep theoretical and practical understanding of CUDA, Triton, high-performance C++ DSP libraries, and multi-threaded parallel computation paradigms.
• Understanding of inference serving (vLLM, TensorRT-LLM, Triton Inference Server, SGLang) and what matters including batching, KV cache management, and latency versus throughput tradeoffs.
• Scale-Out Infrastructure Knowledge: Demonstrated familiarity with HPC scale-out infrastructures, distributed memory architectures, and networking protocols designed for high-performance clustering.
• Prior experience at accelerated software, cloud, or startup organizations building complex AI compute systems, such as NVIDIA, Meta, Google, AWS, SambaNova, Cerebras, Groq, or Lightning AI.
  
  

• MBA or equivalent experience in technology commercialization or product strategy.
• Active contributions to open-source AI infrastructure projects, compilers (MLIR/LLVM), or performance optimization libraries.
• Direct experience working inside a frontier AI lab or foundation model organization (e.g., OpenAI, Anthropic, xAI, Google DeepMind) developing large-scale distributed systems.