Swing Consulting Ltd.
Platform Engineer (AI / Data Platform, 30-40K)
Build and maintain the AI platform and data lakehouse, automating operations and deploying services using Python, Kubernetes, and MLOps tools.
- Compensation
- HK$30K–HK$40K / yr
- Location
- Hong Kong, Hong Kong
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Degree holder in computer science, software engineering, or related fields.
- At least 4 years of experience in platform / backend development.
- Experience in the following technology stack is a must:
- Scripting: Python, Bash, SQL;
- Infrastructure: Docker, Terraform, Helm, Kubernetes ;
- CICD: Jenkins, Git, Ansible
- Experience in delivery of AI platform or data platform in a large-scale enterprise environment is a must.
- Knowledge of DataOps/MLOps is a must.
- Experience in public cloud platform (AWS, Azure, AliCloud).
- Experience in the following technology stack is preferable:
- Monitoring: Grafana, Loki, Prometheus;
- Test Framework: jMeter, jUnit, PyTest;
- Vector DB: Weaviate, Milvus, ElasticSearch, Qdrant, etc.;
- AI Orchestration: Langchain, LlamaIndex, LangGraph etc.;
- AI Platform: Jupyter, MLFlow, Ray, vLLM, Dify;
- Data Lakehouse: Airflow, Spark, Hive Metastore, Iceberg;
- DevSecOps Suite: JIRA, Sonar, Nexus, Harbor, etc.
- Experience in working with an international team, with solid grounding in financial service is a plus.
- Excellent communication skills in Cantonese, English, and Mandarin.
Full description
SW5959 |16 Apr 2026
Responsibilities
- Assist in, and automate whenever possible, the day-to-day operation of the AI Platform and Data Lakehouse.
- Contribute in AI Platform and Data Lakehouse development, including monitoring, logging and deployment of proprietary, open-source or in-house developed applications.
- Develop services and integrate them with internal and external APIs / MCPs.
- Identify and evaluate new technologies that improve performance maintainability and scalability of our infrastructure.
- Conduct platform proof-of-concept (PoC) and acceptance testing.
- Provide visibility into the structure, state and performance of the AI platform and Data Lakehouse.
- Work closely with Architects, Platform Engineers and Product Owners to deliver software in a continuous delivery environment.
- Work closely with AI Engineer, Data Engineer and business stakeholders to assist in the development and deployment of AI application and data pipeline.
Qualifications & Experience
- Degree holder in computer science, software engineering, or related fields.
- At least 4 years of experience in platform / backend development.
- Experience in the following technology stack is a must:
- Scripting: Python, Bash, SQL;
- Infrastructure: Docker, Terraform, Helm, Kubernetes ;
- CICD: Jenkins, Git, Ansible
- Experience in delivery of AI platform or data platform in a large-scale enterprise environment is a must.
- Knowledge of DataOps/MLOps is a must.
- Experience in public cloud platform (AWS, Azure, AliCloud).
- Experience in the following technology stack is preferable:
- Monitoring: Grafana, Loki, Prometheus;
- Test Framework: jMeter, jUnit, PyTest;
- Vector DB: Weaviate, Milvus, ElasticSearch, Qdrant, etc.;
- AI Orchestration: Langchain, LlamaIndex, LangGraph etc.;
- AI Platform: Jupyter, MLFlow, Ray, vLLM, Dify;
- Data Lakehouse: Airflow, Spark, Hive Metastore, Iceberg;
- DevSecOps Suite: JIRA, Sonar, Nexus, Harbor, etc.
- Experience in working with an international team, with solid grounding in financial service is a plus.
- Excellent communication skills in Cantonese, English, and Mandarin.
Benefits
- 30-40K Depends on Experience
- 10-20 Days Annual Leave
- 5-day Work Week