AI Tech Architect

Job description

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

Required Skill Profession

Other General