AI Tech Architect

Get AI-powered advice on this job and more exclusive features. Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services companies. We provide comprehensive consulting solutions, as well as middle- and back-office support, to empower our clients with streamlined operations and cutting-edge strategies. With a global team of over 2,000 professionals, Hytech has established a strong presence worldwide, with offices in Australia, Singapore, Malaysia, Taiwan, Philippines, Thailand, Morocco, Cyprus, Dubai and more. Introduction We are looking for experienced and forward-thinking AI Architects to join the design and implementation of scalable, cloud-native AI infrastructure. In this role, you will be responsible for setting up robust MLOps pipelines, building multi-modal feature platforms (including vector, graph, and sequence data stores), and delivering production-grade model training and deployment workflows . You’ll work closely with engineering, product, and data teams to leverage cloud infrastructure (e.g., , AWS (Main), AliCloud, GCP, Azure, ) to deliver scalable, cost-efficient, and secure AI systems. Key Responsibilities Architect and build end-to-end AI infrastructure across model lifecycle stages — from feature engineering to model training, deployment, and monitoring — using cloud-native technologies . Design and maintain feature pipelines for: Vector databases (e.g., FAISS, Weaviate, Milvus) for semantic embedding retrieval Graph databases (e.g., Neo4j, TigerGraph) for network-based inference and entity linking Sequence/time-series databases (e.g., InfluxDB, TimescaleDB) for temporal pattern modeling and real-time monitoring Lead the design of a centralized feature store platform to support consistent, reusable ML features across teams. Develop MLOps workflows using cloud orchestration tools and infrastructure-as-code to automate training, validation, deployment, and monitoring. Leverage AWS, AliCloud, GCP, and Azure services (e.g., SageMaker, Vertex AI, EAS, GKE, ECS) to optimize infrastructure for scalability, availability, and cost. Integrate model serving platforms (e.g., Triton, Ray Serve, BentoML, vLLM) for low-latency inference at scale. Establish observability for ML pipelines: model drift, feature staleness, and data quality monitoring. Collaborate with AI Scientist and application teams to productionize new models and LLM-based systems. Basic Qualifications Bachelor’s or Master’s degree in Computer Science , Machine Learning , or Systems Engineering . 6+ years of experience in building AI/ML platforms , cloud-native architecture , or infrastructure engineering . Hands-on experience with: Feature stores: Feast , Tecton , custom in-house platforms Container orchestration and deployment using Docker and Kubernetes Deep understanding of distributed systems, CI/CD for ML, and scalable data & model pipelines. Preferred Qualifications Practical experience with multi-database architecture: Graph DBs : ArangoDB, NebulaGraph, Neo4j, MemGraph Experience supporting LLM and embedding model deployments (e.g., vLLM, DeepSpeed, HuggingFace inference endpoints) Familiarity with GPU scheduling, cost optimization, and hybrid/multi-cloud architecture patterns. Contributions to internal platforms or developer tools enabling teams to deploy models autonomously. Proven ability to drive infra decisions across cross-functional teams in a fast-paced environment. What We Offer Competitive compensation and equity package. Ownership to design foundational AI infrastructure across cloud and hybrid environments. Opportunity to shape the next generation of scalable AI systems from infrastructure to application layer. Collaboration with world-class engineers, researchers, and domain experts. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information Technology, Engineering, and Analyst Industries Securities and Commodity Exchanges, Computer and Network Security, and IT System Data Services Referrals increase your chances of interviewing at Hytech by 2x Get notified about new Technical Architect jobs in Singapore, Singapore . Frontend Engineer - Marketplace, Web Frontend Platform Software Engineer (Frontend, Backend, or Full stack) Web Frontend Engineer（Work Location: Remote in Taiwan) Back-end Software Engineer (On-site ) We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr