Information Technology Infrastructure Engineer

Job Summary 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.

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