Description

Responsibilities

• Lead the engineering team responsible for the AI platform and its supporting services.
• Own the reliability, security, scalability, and operational health of the platform
• Translate architectural direction into maintainable and supportable engineering solutions
• Implement and operationalize engineering standards through automated testing and quality gates, deployment tooling, and operational readiness practices
• Lead cloud platform, CI/CD, and deployment practices for AI workloads
• Define and maintain monitoring, logging, and observability standards across the platform
• Partner with security, infrastructure, and architecture teams to ensure compliance with enterprise standards
• Balance business priorities, platform improvements, operational stability, and technical debt when planning platform delivery
• Provide mentoring, coaching, and technical leadership to platform engineers
• Improve the developer experience for the AI engineering teams who build agents and AI solutions on the platform; providing reusable services, templates, frameworks, and documentation for them to build on
• Review high-risk technical changes and provide guidance on complex engineering decisions
• Evaluate new technologies and platform capabilities that could improve security, reliability, productivity, or scalability
• Promote knowledge sharing and engineering best practice across the AI CoE

Qualifications
12yrs + experience in software engineering, platform engineering, cloud engineering, machine learning engineering, or a related technical discipline

• Demonstrated experience providing technical leadership for enterprise platforms, distributed systems, or cloud-native solutions
• Experience building, supporting, or operating AI, machine learning, or generative AI solutions in production environments
• Strong understanding of modern software engineering principles, distributed systems, APIs, microservices, event-driven architectures, and cloud-native development
• Experience with at least one major cloud platform (AWS preferred; Azure or GCP experience also welcomed)
• Experience with Infrastructure-as-Code approaches, containerisation, and modern deployment practices
• Experience implementing CI/CD, automation, monitoring, and operational practices for enterprise applications or AI-enabled solutions
• Understanding of AI platform components such as vector databases, retrieval systems, orchestration frameworks, model serving, or related technologies
• Familiarity with agentic AI, AI orchestration frameworks, or emerging AI platform capabilities would be beneficial
• Experience establishing engineering standards, governance practices, and operational processes
• Experience in platform security, access management, risk management, cost and operational governance
• Strong communication and stakeholder management skills, with the ability to work across engineering, architecture, business, and security teams

Key Skills

Education

Bachelor's degree