AI Tech Architect

Job description

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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

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Required Skill Profession

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