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Department 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. The Front Office AI Technology team is focused on enabling the development of AI capabilities within the investment environment. The team partners closely with Front Office stakeholders to identify, design, and develop AI-enabled solutions that enhance decision‑making, efficiency, and insight, while operating within the firm’s risk, control, and regulatory constraints. 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. Role overview: 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. The role exists to accelerate public cloud-based AI maturity and support existing on-premise platforms, while enabling enterprise and Front Office AI use cases through robust, well‑governed infrastructure. 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. This role offers a compelling opportunity to operate at the intersection of AI innovation and institutional‑grade infrastructure, enabling next‑generation AI capabilities within the investment environment of a leading hedge fund. Experience required: Public Cloud Platform Engineering (Azure/AWS/GCP) 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 / Gemini alongside existing cloud platforms. AI Platform Operations & Integration Proven experience building, running, and supporting AI services across public cloud (Azure, AWS, GCP, etc.) and enterprise SaaS AI platforms (OpenAI Enterprise, Anthropic, etc.). Strong understanding of AI operational patterns including API-based model access, availability, monitoring, and governance rather than model development or data science. On-Premise Platform Engineering, Operations & Integration Proven experience building, running, and supporting on-premise platforms and foundational services, such as advanced virtualisation with VMWare, Hyper-V and/or Kubernetes Enterprise and data platform integration experience between on-premise and public cloud, in aspects of security, high availability, networking, load balancing to deliver hybrid applications and infrastructure Cloud Networking & Hybr