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.