AI Cloud Platform Engineer

📋 Job Overview

This role sits at the intersection of our Front Office AI Technology team and Technology Infrastructure. This role straddles both teams, operating as the delivery and implementation function for our central AI capacity within the broader Infrastructure department. The position is responsible for deploying and operationalising the Front Office AI Technology team’s requirements by working hands‑on with Technology Infrastructure to design, build, automate, and run AI‑ready cloud platforms in production.

🏢 About BlueCrest Capital Management

Our Technology Infrastructure team operates globally and is responsible for every aspect of the firm's hybrid platform. This ranges from our EUC/Office environments to Trading and Core service Co-Location Data Centres, and extends to Public Cloud, delivering top-tier technology services to a dynamic and demanding Trading organisation.

In addition to meeting the round-the-clock operational demands of the platforms, we continuously evolve and transform our platforms to maintain a competitive edge that our business requires. We innovate to provide valuable solutions and leverage our skilled Technology teams to deliver against rapidly changing business requirements.

🎯 The Role

The AI and Public Cloud Engineer is a highly technical, hands‑on platform engineering role responsible for designing, building, automating and operating secure cloud and AI platform foundations across a hybrid environment.

✅ Key Responsibilities

• Working across Microsoft Azure, on-premise platforms and later with AWS and GCP Gemini / VertexAI enablement, the role delivers secure by design platforms covering identity, networking, security, governance, automation, and cost control.
• The position focuses on the operational reality of AI services with supporting, integrating, and governing AI platforms and AI SaaS providers within a low risk tolerance, regulated environment.

📌 Required Qualifications

• Deep hands-on experience engineering and operating Azure and/or AWS landing zones, including identity, networking, security baselines, governance and hybrid connectivity.
• Proven experience building, running, and supporting AI services across public cloud (Azure, AWS, GCP, etc.) and enterprise SaaS AI platforms (OpenAI Enterprise, Anthropic, etc.).
• Proven experience building, running, and supporting on-premise platforms and foundational services, such as advanced virtualisation with VMWare, Hyper-V and/or Kubernetes
• Hands-on experience designing and operating hybrid cloud connectivity (ExpressRoute / Direct Connect), including resilient routing, segmentation and private access patterns.
• Deep experience implementing cloud IAM (Azure Entra ID, AWS IAM), RBAC, privileged access, MFA and workload identity patterns.
• High proficiency in Infrastructure as Code (Terraform, Bicep, CloudFormation/CDK) to deliver repeatable, governed cloud or on-premise platforms.
• Strong scripting or development capability (Python, Bash, PowerShell) to automate platform operations, integrations, and CI/CD workflows.
• Experience implementing governance frameworks including policy enforcement, tagging standards, compliance automation and environment guardrails.
• Practical experience managing cost controls and consumption optimisation, particularly for AI and data-intensive workloads.
• Hands-on experience applying data classification, DLP, and AI usage controls to protect sensitive data across cloud and SaaS AI services.
• Demonstrated experience supporting production cloud and on-premise platforms, including incident response, resilience testing and operational improvement.

⭐ Desirable Experience

• Working knowledge of GCP infrastructure sufficient to deploy, integrate, and operate Vertex AI / Gemini alongside existing cloud platforms.
• Strong understanding of AI operational patterns including API-based model access, availability, monitoring, and governance rather than model development or data science.
• Strong practical knowledge of cloud network security, private endpoints, DNS integration, egress control and zero-trust networking principles.
• Working knowledge of enterprise AI security and governance standards aligned to regulated or low risk tolerance environments.
• Ability to balance critical BAU support with ongoing platform engineering and transformation work in time‑sensitive environments.

🎁 Benefits

BlueCrest is committed to providing an inclusive environment for its workforce. As an employer, we provide equal opportunities to all people regardless of their gender, marital or civil partnership status, race, religion or ethnicity, disability, age, sexual orientation or nationality.

🛂 Visa & Eligibility