AI Engineer – Technical Leader (Agentic AI & FPGA Systems)

Build enterprise-grade RAG pipelines for knowledge integration and retrieval

Define system-level architecture bridging cloud, edge, and hardware acceleration

Agentic AI & LLM Development

Develop advanced agent workflows, including:

• Tool-using agents
• Planning and reasoning agents
• Multi-agent collaboration systems

Evaluate and integrate state-of-the-art LLMs (open-source and proprietary)

Optimize prompting, memory, and reasoning strategies for performance and reliability

AI Model Optimization on FPGA (Core Focus)

Lead AI model optimization and deployment on FPGA platforms, including:

• Quantization (INT8 / BF16 / mixed precision)
• Graph compilation and operator fusion
• Model partitioning across CPU/GPU/FPGA
• Memory and bandwidth optimization

Develop workflows to map AI models (e.g., CV, LLM inference) from PyTorch/Hugging Face to FPGA

Enable low-latency, high-efficiency inference pipelines on FPGA-based systems

Collaborate with hardware teams to align model architecture with FPGA constraints (DSP, BRAM, interconnect)

Hardware-Aware AI Co-Design

Co-design AI systems with:

• FPGA acceleration
• ASIC platforms
• Heterogeneous compute architectures (CPU/GPU/FPGA)

Integrate AI workflows into EDA toolchains and hardware design flows

Drive innovations in software-hardware co-optimization

Framework & Platform Development

Build internal AI platforms leveraging:

• LangChain
• LlamaIndex
• Custom agent orchestration frameworks​

Develop reusable components for:

• Memory management
• Tool integration
• Knowledge retrieval and indexing​

Enable scalable deployment pipelines for AI applications on FPGA

Technical Leadership

Lead architecture design reviews and set technical direction

Mentor senior engineers and guide cross-functional teams

Drive innovation at the intersection of AI systems and semiconductor platforms

What Makes This Role Unique

Define agentic AI architecture for hardware-native AI systems

Work at the frontier of:

AI reasoning systems

FPGA-based acceleration

Next-generation computing platforms

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High-impact role shaping AI + semiconductor convergence

Impact

You will enable a new class of intelligent systems where AI agents are tightly coupled with hardware, delivering:

Real-time decision-making pipelines

Efficient, scalable AI deployment on FPGA

End-to-end automation from model to hardware execution

Summary

This role is ideal for a senior technical leader who can:

Bridge LLM + Agentic AI + RAG with FPGA/ASIC system architecture

Drive AI model optimization and deployment on FPGA

Lead innovation in next-generation AI + hardware integrated systems

Qualifications:

Required

Strong experience in LLMs, agentic AI, or RAG systems

Proven track record in large-scale AI system architecture and deployment

Solid programming skills in Python/C++ and modern AI frameworks

Experience designing distributed or production AI systems

Strong system-level thinking across software and infrastructure

Preferred / Plus

Experience with FPGA, ASIC, or hardware acceleration platforms

Familiarity with FPGA development flows and toolchains (e.g., synthesis, compilation, HLS, runtime)

Experience with AI model optimization for hardware (quantization, compilation, deployment)

Exposure to EDA tools and semiconductor design workflows

Background in heterogeneous computing systems (CPU/GPU/FPGA)

Job Type:

Regular

Shift:

Shift 1 (China)

Primary Location:

Shanghai, China

Additional Locations:

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.