Infrastructure Consultant - Cloud

Primary Responsibilities

• Execute projects within the designated practice to fulfill requirements for platform availability, reliability, and resilience.
• Convert business needs into platform infrastructure designs.
• Collaborate with service providers to architect, deploy, and configure resilient, available, and secure AI infrastructure.
• Ensure adherence to the Authority's Enterprise Architecture and Security Standards, along with IM8 and AI Policies.
• Serve as the primary contact for new AI product initiatives, facilitating system design, integration, acceptance, and performance testing.
• Oversee AI platform operations and respond to inquiries from Data Scientists and Product Managers.
• Enhance operational runbooks, SOPs, and comply with enterprise and regulatory requirements.
• Continuously enhance the AI platform experience by introducing new features and improvements.
• Simplify product development and operations through automation and the creation of reusable services.
• Contribute to AI Platform design reviews and the enhancement of AI, OS, container, and database security standards.
• Onboard hosting environments by designing, establishing, configuring, implementing, testing, and commissioning the necessary infrastructure.
• Oversee system architecture, resource planning, platform performance, and hosting across servers, operating systems, and containers, excluding hypervisor and storage layers.

Qualifications We Seek

• Exceptional written and verbal communication abilities, capable of pitching ideas, influencing stakeholders, and balancing strategic perspectives with business needs and challenges.
• Proven capability to evaluate project and compliance requirements and create practical, sustainable solutions.
• Hands-on experience in constructing, securing, and managing enterprise Data Science and AI platforms on AWS or in on-premises environments.
• Practical experience in building and managing DevSecOps, MLOps, and/or LLMOps pipelines.
• Experience with AI and container services, LLM inference, and preferred familiarity with Linux.
• Proficiency in Infrastructure-as-Code, automation, and the Python tech stack is preferred.
• Experience with Identity & Access Management services (e.g., Entra ID, AWS Cognito, and AWS IAM) and Monitoring & Observability services (e.g., CloudWatch, Splunk, and Elastic) is advantageous.
• Knowledge of PostgreSQL, vector databases, object storage, and processing of both structured and unstructured datasets is beneficial.
• Solid understanding of AI, application, and infrastructure security risks and controls.