Principal / Staff AI Systems Architect (LLM, Search, RAG & …, Singapore

Company Overview
Our client is a leading global technology organization investing heavily in next-generation AI capabilities across large language models, search and recommendation systems, AI agents, and high-performance computing infrastructure. As part of its continued expansion in Singapore, the company is looking to appoint multiple Principal / Staff AI Systems Architects to join its growing team. Job Description
Reporting to senior technical leadership, you will play a critical role in designing and optimizing end-to-end AI systems across the full stack, from model architecture and inference optimization to distributed systems and large-scale production deployment. You will focus on building high-efficiency AI computing systems, improving performance, scalability, and cost efficiency of large-scale AI workloads in real-world environments. Key Responsibilities
1. AI Systems Architecture & Optimization Design and optimize large-scale AI systems across model, system, and infrastructure layers Improve model inference efficiency through techniques such as quantization, sparsity, KV cache optimization, and distributed parallelism Ensure low latency, high throughput, and cost-efficient deployment in production environments 2. High-Efficiency AI Computing Develop and optimize large-scale inference systems for LLMs and multimodal models Work on GPU acceleration, CUDA optimization, and distributed computing frameworks Drive performance improvements across compute, memory, and networking layers 3. Search, Recommendation & RAG Systems Build scalable AI-powered search and recommendation platforms Develop retrieval-augmented generation systems with strong grounding and hallucination control Enable multilingual and cross-regional search experiences Support personalization and monetization use cases such as recommendation and advertising 4. AI Agent Systems & Security Contribute to AI agent system design and orchestration Implement safeguards including prompt injection prevention, access control, and system robustness Ensure secure and reliable deployment of AI systems 5. End-to-End System Ownership Drive technical initiatives from design to production deployment Collaborate with cross-functional teams across global engineering and product organizations Deliver measurable impact on large-scale production systems Requirements
Qualifications & Experience Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field 5-12+ years of experience in AI systems, machine learning infrastructure, or distributed computing Strong experience working with large-scale production systems Technical Skills Strong expertise in LLMs or multimodal models Hands-on experience in inference optimization or high-efficiency computing Solid programming skills in Python and/or C++ (CUDA experience preferred) Experience with modern AI frameworks and distributed systems Preferred Experience Experience in search, recommendation systems, or RAG architectures Familiarity with AI agent systems and orchestration frameworks Exposure to large-scale infrastructure such as GPU clusters or cloud-based AI platforms Key Competencies
Strong systems thinking across both low-level optimization and high-level architecture Ability to work independently as a senior individual contributor Comfortable operating in a fast-paced, global environment Strong problem-solving and technical leadership capabilities Additional Information
Opportunity to work on cutting-edge AI systems with global impact Exposure to large-scale real-world AI applications Collaborative and innovation-driven environment