AI Cloud Platform Engineer
BlueCrest Capital Management2 months ago
London, United KingdomSenior
Responsibilities
- Design, build, automate, and operate secure AI-ready cloud platforms across hybrid environments.
- Engineer and operate Azure and/or AWS landing zones covering identity, networking, security baselines, governance, and hybrid connectivity.
- Deploy, integrate, support, and govern AI services and enterprise AI SaaS platforms across public cloud and on-premise environments.
- Build and support on-premise platforms and foundational services, including virtualization and Kubernetes environments.
- Design hybrid connectivity, resilient routing, network segmentation, private access, DNS integration, egress controls, and zero-trust network security.
- Implement cloud IAM, RBAC, privileged access, MFA, workload identity, least-privilege access, auditability, and sensitive-data controls.
- Use infrastructure as code and scripting to automate platform operations, integrations, and CI/CD workflows.
- Implement policy enforcement, tagging, compliance automation, environment guardrails, data classification, DLP, AI usage controls, and cloud cost optimization.
- Support production cloud and on-premise platforms through incident response, resilience testing, operational improvement, and ongoing transformation work.
Requirements
- Deep hands-on experience engineering and operating Azure and/or AWS landing zones, including identity, networking, security baselines, governance, and hybrid connectivity.
- Working knowledge of GCP infrastructure sufficient to deploy, integrate, and operate Vertex AI and Gemini alongside other cloud platforms.
- Proven experience building, running, and supporting AI services across public cloud and enterprise SaaS AI platforms such as OpenAI Enterprise and Anthropic.
- Strong understanding of operational AI patterns including API-based model access, availability, monitoring, and governance rather than model development or data science.
- Proven experience supporting on-premise platforms and foundational services such as VMware, Hyper-V, and/or Kubernetes.
- Experience integrating enterprise and data platforms between on-premise and public cloud across security, high availability, networking, and load balancing.
- Hands-on experience with hybrid connectivity such as ExpressRoute and Direct Connect, including resilient routing, segmentation, and private access patterns.
- Deep experience implementing Azure Entra ID, AWS IAM, RBAC, privileged access, MFA, and workload identity patterns.
- High proficiency with Terraform, Bicep, CloudFormation, and/or CDK for repeatable, governed platform delivery.
- Strong scripting or development capability in Python, Bash, and/or PowerShell for platform automation and integrations.
- Experience implementing governance frameworks, compliance automation, data classification, DLP, AI usage controls, and cost optimization for AI and data-intensive workloads.
- Demonstrated experience supporting production platforms, including incident response, resilience testing, and operational improvement.
- Excellent communication and organizational skills, with the ability to work independently and across infrastructure, cybersecurity, application development, and front-office teams.