Summary
✨ AI‑Generated
Support enterprise-grade AI, generative AI, and data platform infrastructure as an AI Platform Support Engineer. You will provide L1/L2 operational support, manage incidents and root-cause analysis, oversee release and model lifecycle processes, and help maintain stable, highly available services across secure hybrid cloud and on-premises environments. Experience with platform operations, cloud or on-prem systems, data platforms, or SRE is expected.
Highlights
A 12-month role supporting enterprise AI and data platforms in a high-security environment, with exposure to cloud and on-premises infrastructure, model lifecycle operations, incident management, and high-availability services.
Description
AI Platform Support Engineer (2-6 Yrs)
Role Details
Position Title: AI Platform Support Engineer x 3Client Type: Top-Tier Financial Services EnterpriseLocation: Hong Kong (Onsite - Central)Employment Type: 12 month contractExperience Required: 2-6 years in Platform Support, Cloud/On-Prem Systems, Data Platforms, or SREPosition Overview
We are seeking 3 AI Platform Support Engineer to drive operational excellence, system stability, and release management across enterprise-grade AI, GenAI, and Data Lake infrastructures.
Operating within a high-security hybrid and on-premises cloud environment, you will play a pivotal role in maintaining L1/L2 platform stability, overseeing model lifecycle pipelines, and ensuring high availability for business-critical AI services.
Key Responsibilities
Platform Operations & L1/L2 Support: Lead L1/L2 support, incident management, root-cause analysis, and escalation pathways for enterprise AI applications, GenAI solutions (e.g., Azure OpenAI, RAG architectures), data lake infrastructure, and data science environments.Hybrid Infrastructure & Patch Management: Execute routine patch management, version upgrades, and system maintenance across relational and vector databases, AI support tools, and hybrid/on-prem infrastructure.Release & Deployment Management: Oversee production deployments, CI/CD execution, change verifications, and rollback procedures in compliance with enterprise change management protocols.Monitoring & Platform Reliability: Monitor system performance, model endpoints, streaming data pipelines, and platform availability using enterprise monitoring stacks (Prometheus, Grafana, CloudWatch).Cross-Functional Collaboration: Partner closely with AI Engineers, Data Scientists, and Infrastructure leads to support model lifecycle management (MLOps) and data platform workflows.Automation & Process Optimization: Identify support bottlenecks and develop Python/Shell automation to streamline internal operations and support workflows.Key Requirements
Education: University degree in Computer Science, Information Technology, Data Engineering, Artificial Intelligence, or related disciplines.Experience: 2-6 years of relevant hands-on experience in application support, platform support, cloud/on-prem systems, or data platforms.Technical Stack:Infrastructure & DevOps: Enterprise Cloud (AWS, Azure, Alibaba Cloud) and On-Prem Hybrid environments; Docker, Kubernetes; Git, Jenkins, JIRA.AI & GenAI Solutions: Azure OpenAI, AWS Bedrock, Dify, RAG architecture, MLflow, Ray Serve.Data Platforms: Apache Airflow, Apache Spark, Hive, Apache Iceberg.Databases & Access: PostgreSQL, Vector Databases (Weaviate or equivalent), Keycloak IAM.Programming & Web: Python, SQL, Shell scripting (Bash), Node.js / Next.js.Monitoring: Prometheus, Grafana, CloudWatch, or equivalent tools.Domain Advantage: Prior experience managing L1/L2 support in regulated financial institutions or enterprise hybrid environments with strict DevSecOps/CI/CD pipelines.Soft Skills: Strong analytical problem-solving skills; excellent communication to engage with both technical teams and non-technical business stakeholders.Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.
Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.
