Systems Analyst (Cloud-Native)

About Us

EDPS Systems Limited is a Hong Kong-based company, now developing its own in-house AI products. We are building a dedicated team to design, build and run these products in the cloud.

The role

You will work on the end-to-end integration of our in-house AI products, bringing devices, data pipelines, APIs, databases, AI/ML services and web and mobile apps together on one cloud-native platform. This is a hands-on role: you will design, build, deploy and operate cloud-native services, and keep them secure, scalable and well documented. You will work closely with our software engineers, data scientists and external technology partners.

Key responsibilities

• Design and deliver the end-to-end integration architecture for our AI products, from data ingestion through cloud APIs, data stores and ML services to web and mobile applications.

• Build cloud-native services on AWS using microservices, containers (Docker, ECS/EKS) and serverless components (e.g. Lambda, API Gateway), designed for scalability, resilience and cost efficiency.

• Automate infrastructure and releases with infrastructure-as-code and CI/CD pipelines.

• Build and maintain RESTful APIs, event-driven messaging and ETL pipelines across NoSQL and relational databases.

• Integrate AI/ML components, such as model serving and document-processing services, taking them from prototype to production.

• Set up and manage development, staging and production environments, and own observability (monitoring, logging, alerting), backup and incident response.

• Implement cloud security controls for sensitive personal data: role-based access, encryption, audit trails and PDPO compliance.

• Integrate third-party devices and vendor systems, and write integration specifications, API documentation and system integration documents.

• Provide technical guidance to engineers, review pull requests and integration designs, and contribute to sprint planning and technical risk assessment.

Requirements

• Degree in Computer Science, Computer or Electronic Engineering, Information Technology or a related discipline.

• Minimum 8 years of hands-on system integration experience (8-9 years preferred), including end-to-end delivery of multi-component platforms.

• MUST: Proven Cloud-Native development and deployment experience, having designed, built and deployed production workloads on AWS (preferred), Azure or GCP using microservices, containers and serverless services.

• Strong with Docker, Kubernetes or ECS/EKS, CI/CD pipelines (e.g. GitHub Actions, Jenkins) and infrastructure-as-code (Terraform, CloudFormation or CDK).

• Solid backend development in Python and/or Node.js or Java; RESTful API design; event-driven architecture and messaging (e.g. MQTT, Kafka, SQS/SNS).

• Hands-on with MongoDB and PostgreSQL (or equivalents), and with building data pipelines and ETL.

• Good knowledge of cloud security and observability: IAM, network segregation, encryption, secrets management, monitoring, logging and audit.

• Able to write clear technical documentation, such as API specifications and system integration documents.

• Good command of written and spoken English and Chinese (Cantonese); Mandarin is an advantage.

Advantageous

• IoT device integration and real-time data streaming.

• Putting ML models into production (MLOps, model serving, AWS SageMaker) and using cloud AI services such as document AI.

• Data and ML pipeline tooling: Apache Airflow for workflow orchestration and MLflow for experiment tracking, model registry and deployment.

• Managed cloud data services (e.g. MongoDB Atlas, data lakes).

• Experience in healthcare or other domains handling sensitive personal data.

• AWS Certified Solutions Architect or DevOps Engineer (Professional), Kubernetes (CKA/CKAD) or equivalent; exposure to ISO 27001.

• Agile/sprint delivery, mentoring engineers, or working in a start-up or incubator environment.