ARTIFICIAL INTELLIGENCE PLATFORM ENGINEER
Job Description
Job purpose
The AI Platform Engineer builds and maintains the shared technology foundation used to develop, test and run the Bank’s AI solutions. The role configures approved computing environments, platform services, access and connectivity with ICT and Cybersecurity, and provides reusable tools for model and engineering teams. It focuses on platform capability, security, capacity and resilience, working with ML Ops on service operation and with ML Engineers on solution requirements
Principal responsibilities
Translate approved AI workload requirements into platform designs, capacity estimates and implementation plans with ICT and architecture owners.
Build and configure approved compute, storage, networking and platform services for development, testing and production environments.
Create reusable, version-controlled infrastructure configurations and environment templates to reduce manual setup and configuration drift.
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Integrate identity, role-based access and service accounts with approved bank controls; separate user, administrator and workload permissions.
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Implement approved connectivity, encryption and secrets-management controls with ICT and Cybersecurity; retain configuration evidence.
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Configure shared tools for development, experiment tracking, artefact storage and model serving, with clear service ownership and support boundaries.
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Provide approved access to generative AI services with usage limits, logging and data-handling controls aligned to permitted business use.
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Assess platform compatibility, scalability and performance under expected workloads; document constraints and recommend capacity improvements.
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Build platform health metrics and alerts for resource use, availability and infrastructure faults; hand over operational monitoring to ML Ops.
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Test platform upgrades, patches and dependency changes in controlled environments before authorised release with ICT and ML Ops.
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Engineer and test backup, restore and resilience arrangements against approved service requirements with ICT and continuity owners.
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Resolve platform defects and supplier issues, supporting incident diagnosis while ML Engineers address solution code and Data Scientists address model behavior.
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Maintain platform architecture, configuration records, runbooks and handover evidence; support security review and independent assurance requests.
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