Senior AI System Engineer %28HW/SW Co-Design, Servers & Racks%29

Key Responsibilities

• End-to-End System Definition: Define the holistic, system-level specifications for AI inference servers and rack deployment form-factors, harmonizing mechanical, electrical, thermal, firmware, and software requirements.
• Hardware-Software Co-Design: Collaborate intensely with silicon architects, compiler teams, and cloud-software developers to optimize workload execution pipelines. Define software abstraction layers, runtime behaviors, and driver boundaries that match the physical memory constraints and compute structures of the hardware.
• Bleeding-Edge HW Architecture Definition: Drive the architectural boundaries for multi-layer PCBs and multi-chip modules, ensuring optimal configurations for ultra-high-speed interfaces:
• Interconnects & Fabric: PCIe Gen6 / Gen7, CXL, and multi-die topologies %28UCIe%29.
• Hyperscale Networking: 400G / 800G / 1.6T Ethernet cluster setups.
• Next-Gen Memory: Ultra-fast parallel memory sub-systems including LPDDR6 / LPDDR6x and HBM.
• Power & Liquid Thermal System Definitions: Architect high-power density infrastructure parameters, specifying multiphase voltage regulator modules %28VRMs%29 running at ultra-low core voltages %28<0.8V%29. Define system mechanical boundaries for direct-to-chip liquid cooling assemblies and cold plate layouts.
• Tier-1 & Ecosystem Management: Lead technical alignment and hand-off specifications with Tier-1 server and rack manufacturers %28e.g., Foxconn, Quanta, Supermicro, Wiwynn%29. Author crisp, rigorous Hardware/Software Interface %28HSI%29 documents and system integration guides.
• Validation & Compliance Strategy: Blueprint full-stack system validation plans, specifying how early emulation models, post-silicon bring-up, thermal profiling, and AI workload benchmarks must interact to guarantee deployment-ready stability.

Key Requirements & Qualifications

• Education & Experience: Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a highly related field, with 7+ years of cross-disciplinary hardware/software systems engineering experience specifically within server, cloud, or enterprise data center platforms.
• True Full-Stack HW/SW Fluency: A proven career history that successfully spans both worlds:
• Hardware Domain: Deep architectural knowledge of high-speed SerDes, power delivery networks %28PDN%29 for hundreds of amps, signal/power integrity rules, and liquid cooling mechanics.
• Software Domain: Solid grasp of deep learning compilation frameworks %28e.g., Triton, TVM%29, kernel-level drivers, memory layout orchestration, and distributed data center execution patterns %28Kubernetes, Ray%29.
• Tier-1 Server & Cluster Infrastructure Experience: Direct experience working closely with Tier-1 server ODMs on high-density system integration, board-to-board topologies, power management, and server rack-level infrastructure scaling.
• Protocol & Standards Mastery: Deep engineering knowledge of modern data center specifications, notably PCIe Gen6/7, Ethernet fabrics up to 1.6T, LPDDR6/6x, and Open Compute Project %28OCP/OAM%29 deployment architectures.
• Startup Agility & Execution: Exceptional capability to thrive in a fast-paced, high-ambiguity startup environment. A pragmatic architect who can balance ultimate technical ideals with aggressive product commercialization windows.