ICT Infrastructure Engineer REQ126-1/2/3

As a Senior Consultant ICT Infrastructure Engineer, you will manage multiple priorities in a fast-paced environment while supporting stakeholder needs and responding effectively 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 on-premises and cloud-based AI platforms.
• Work with various technology teams, including Platform Architecture and Engineering, Cybersecurity, and Data & Collaboration Platforms, to define requirements and integrate scalable, secure, and compliant AI platforms into the 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 enterprise architecture and security standards, as well as applicable technology 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 and Standard Operating Procedures (SOPs), and adhere to enterprise and compliance mandates.
• Continually improve the AI platform experience by implementing new features and enhancements.
• Continually simplify product development and operations through automation and the development of reusable services.
• Assist in AI platform design reviews and the improvement of AI, operating system, 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 perspectives 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 is preferred.
• Hands-on experience with Infrastructure-as-Code (IaC), automation, and Python technology stacks is preferred.
• Experience working with Identity & Access Management services, such as Entra ID, AWS Cognito, and AWS IAM, and Monitoring & Observability services, such as CloudWatch, Splunk, and Elastic, is 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.