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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior/Principal AI Systems Engineer - **Company:** Huawei - **Location:** Dresden, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Abstraction Layers, Artificial Intelligence, Systems Engineering, Program Optimization, Profiling, Distributed Systems, Machine Learning, Performance Tuning, Cloud Platform System, Large Language Models, Multi-Agent Systems, Information Technology, Machine Learning Operations, Microservices - **Published:** July 15, 2026 - **Apply:** https://www.careerjet.de/jobad/de8464b22ea764cc7d545f7d99d456c396 ## About the Role Advanced academic background - BSc/Master/PhD in Computer Science or related fields, with strong foundations in systems engineering or machine learning. ML systems engineering - Deep experience building and integrating inference pipelines into production systems. Agent architecture - Expertise in designing planning loops, memory subsystems, tool-use interfaces, and multi-step reasoning pipelines. AI PC optimization - Strong knowledge of CPU/GPU/NPU pipelines, memory hierarchies, and low-level performance tuning on PC-class hardware. Technical communication - Fluent in English with the ability to communicate complex systems and research concepts clearly to engineers, product teams, and leadership. Good-to-Have (Preferred Qualifications) Distributed systems - Familiarity with RPC frameworks, message buses, microservices, or distributed scheduling for multi-tier agent workloads. Hybrid inference deployment - Experience orchestrating model execution across on-device, near-device, and cloud environments. Agent architecture - Expertise in designing planning loops, memory subsystems, tool-use interfaces, and multi-step reasoning pipelines. Profiling & benchmarking - Skilled in designing and interpreting performance experiments across heterogeneous compute. Model optimization - Experience with quantization, pruning, distillation, and other efficiency-driven transformations. ## Description Huawei's Hilbert Research Center (DRC)'s mission is to explore programming models, operating system and virtualization technologies on multicore heterogeneous architectures and NVM/SCM platforms, aiming to provide a high-performance, reliable abstraction layer for efficient resource utilization. DRC focuses its technical research in the key areas of Smart Mobile, Telecom, Autonomous Driving, Internet of Things, and Industry 4.0. Join us as a Principal AI Systems Engineer (m/f/d) and lead the creation of next-generation agent systems for the AI PC era. In this role, you will drive research into intelligent, autonomous agents capable of operating across heterogeneous compute tiers - from on-device execution to near-device accelerators and cloud-scale reasoning. You will work closely with product teams to translate research breakthroughs into production-ready capabilities, while growing and mentoring a world-class research and development team. Your mission Architect hybrid agent systems - Design agent architectures that seamlessly combine on-device inference, near-device compute (local servers, LAN accelerators), and cloud-scale reasoning to deliver responsive, capable, and context-aware behavior. Lead multi-tier intelligence strategy - Define how agents decide where to run each component (LLM, vision, speech, planning, memory) based on latency, cost, privacy, and hardware availability. Build scalable agent runtimes - Own the architecture of runtimes that coordinate multiple models, sensor inputs, memory subsystems, and decision-making loops across heterogeneous compute tiers. Drive performance across CPU/GPU/NPU/cloud - Lead optimization efforts for latency, throughput, memory footprint, and energy efficiency across AI PCs, edge devices, and cloud clusters. Translate research into production agents - Partner with research teams to evaluate new model architectures and convert them into robust agent behaviors that run efficiently across distributed environments. Mentor and grow the engineering team - Provide technical leadership, architectural guidance, and mentorship to engineers working on inference, agent logic, distributed systems, and hardware-aware optimization. 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