Information Technology Infrastructure Engineer

Sedha Consulting; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Sedha Consulting seeks an ICT Infrastructure Engineer to manage multiple AI platform priorities in a fast-paced setting. You will productionise AI products, host on on‑premises and cloud platforms, and work with security, architecture, and data teams to ensure scalable and compliant infrastructure.

You will translate requirements into robust designs, deploy secure AI infrastructure, and address stakeholder needs with automation, runbooks, and efficient operations.

Qualifications

• Hands-on experience in building and operating AI platforms in cloud/on-prem environments.
• Ability to design secure, scalable infrastructure compliant with policies.
• Strong communication and stakeholder management capabilities.

Responsibilities

• Partner with Data Science and Product Management to productionise AI products on on-premises and cloud platforms.
• Define requirements with Platform Architecture, Cybersecurity, and Data & Collaboration Platforms.
• Deliver projects ensuring availability, reliability and resilience.
• Translate business needs into platform infrastructure designs.
• Manage AI platform operations and respond to stakeholder queries.
• Continually improve automation and reusable services for AI infrastructure.
• Ensure compliance with Enterprise Architecture and Security Standards.

Skills

Communication skills

AWS

DevSecOps

MLOps

LLMOps

Container services

Infrastructure-as-Code

Python

Tools

AWS Cognito

CloudWatch

Splunk

Elastic

PostgreSQL

Vector databases

Job description

As an ICT Infrastructure Engineer, you will manage multiple priorities in a fast-paced environment while supporting stakeholder needs and responding to change. Specifically, you are expected to:

• Partner with Data Science and Product Management teams to productionise and host Data Science and AI products on PE-managed on-premises and cloud AI platforms.
• Work with Technology Group divisions—including Platform Architecture and Engineering, Cybersecurity, and Data & Collaboration Platforms—to define requirements and integrate scalable, secure, and compliant AI platforms into company’s enterprise environment.

Key Responsibilities

• Deliver projects within the assigned practice to meet platform availability, reliability and resilience requirements.
• Translate business requirements into platform infrastructure designs.
• Work with service providers to design, deploy and configure resilient, available and secure AI infrastructure.
• Ensure compliance with the company’s Enterprise Architecture and Security Standards, as well as IM8 and AI Policies.
• Act as the point-of-contact for new AI product initiatives, supporting system design, integration, acceptance and performance testing.
• Manage AI platform operations and address queries from Data Scientists and Product Managers.
• Improve operational runbooks, SOPs and adhere to enterprise and compliance mandates.
• Continually improve AI platform experience by implementing new features and enhancements.
• Continually simplify product development and operations through automation and building reusable services.
• Assist in AI Platform design review and improvement of AI, OS, container and database security standards.
• Onboard hosting environments by designing, setting up, configuring, implementing, testing and commissioning the required infrastructure.
• Manage system architecture, resource planning, platform performance, and hosting across servers, operating systems, and containers, excluding hypervisor and storage layers.

What we are looking for

• Strong written and verbal communication skills, with the ability to pitch ideas, influence stakeholders and balance strategic perspective with business needs and challenges.
• Ability to assess project and compliance requirements and develop practical, sustainable solutions.
• Hands‑on experience building, securing and operating enterprise Data Science and AI platforms on AWS or in on‑premises environments.
• Hands‑on experience building and operating DevSecOps, MLOps, and/or LLMOps pipelines.
• Hands‑on experience with AI and container services, LLM inference and Linux preferred.
• Hands‑on experience with Infrastructure-as-Code, automation and Python tech stack preferred.
• Experience working with Identity & Access Management services (e.g. Entra ID, AWS Cognito and AWS IAM), and Monitoring & Observability services (e.g. CloudWatch, Splunk and Elastic) are advantageous.
• Knowledge of PostgreSQL, vector databases, object storage, and the processing of structured and unstructured datasets is advantageous.
• Good understanding of AI, application and infrastructure security risks and controls.