At a Glance
- Tasks: Design, build, and operate secure AI cloud platforms in a dynamic environment.
- Company: Join a leading hedge fund at the forefront of AI innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and enhance your skills in a fast-paced setting.
- Why this job: Be part of cutting-edge AI technology that transforms investment decision-making.
- Qualifications: Experience in public cloud platforms and AI service delivery is essential.
The predicted salary is between 70000 - 90000 ÂŁ per year.
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 while enabling enterprise and Front Office AI use cases through robust, well‑governed infrastructure. Working primarily across Microsoft Azure 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.
- Cloud Networking & Hybrid Connectivity: Hands-on experience designing and operating hybrid cloud connectivity (ExpressRoute / Direct Connect), including resilient routing, segmentation and private access patterns. Strong practical knowledge of cloud network security, private endpoints, DNS integration, egress control and zero-trust networking principles.
- Identity, Access Management & Security: Deep experience implementing cloud IAM (Azure Entra ID, AWS IAM), RBAC, privileged access, MFA and workload identity patterns. Practical application of security-by-design principles across cloud and AI platforms, including least privilege, auditability and controlled access to sensitive data.
- Infrastructure as Code & Automation: High proficiency in Infrastructure as Code (Terraform, Bicep, CloudFormation/CDK) to deliver repeatable, governed cloud platforms. Strong scripting or development capability (Python, Bash, PowerShell) to automate platform operations, integrations, and CI/CD workflows.
- Governance, Compliance & Cost Management: Experience implementing cloud governance frameworks including policy enforcement, tagging standards, compliance automation and environment guardrails. Practical experience managing cloud 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. Working knowledge of enterprise AI security and governance standards aligned to regulated or low risk tolerance environments.
- Platform Support & Operational Excellence: Demonstrated experience supporting production cloud platforms, including incident response, resilience testing and operational improvement. Ability to balance critical BAU support with ongoing platform engineering and transformation work in time‑sensitive environments.
About you: The ideal candidate is a highly technical, hands-on platform engineer with demonstrable broad-range skills and deep experience in public cloud infrastructure and AI service delivery. You have a proven track record in problem-solving, balancing critical operational support with advanced engineering initiatives in fast-paced, demanding environments. You are passionate about emerging cloud and AI technologies, eager to build innovative solutions that enhance technology performance while naturally understanding the need for rapid delivery balanced against business risk and operational constraints. You appreciate the importance of security, governance, and cost discipline in enterprise cloud deployments, especially when enabling AI capabilities that require strong data protection and regulatory alignment. You have excellent communication and organizational skills, working effectively both independently and as part of cross-functional teams across Technology Infrastructure, Cybersecurity, Application Development, and Front Office stakeholders. Your commitment to continuous improvement is evident in both learning from others and sharing knowledge to enhance team capability and platform maturity.
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.
AI Cloud Platform Engineer in London employer: BlueCrest Capital Management
Contact Detail:
BlueCrest Capital Management Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Cloud Platform Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works in AI or cloud platforms. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to AI and cloud engineering. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI and cloud platforms. Practice explaining your thought process clearly, as communication is key in these roles. We want to see how you tackle problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Cloud Platform Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Cloud Platform Engineer role. Highlight your experience with public cloud platforms like Azure, AWS, and GCP, and showcase any relevant projects that demonstrate your hands-on skills in building and operating cloud infrastructures.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and cloud technologies. Mention specific experiences that align with the job description, especially around governance, security, and automation, to show us you’re the perfect fit.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Include details about your experience with Infrastructure as Code tools like Terraform or Bicep, and any scripting languages you’re proficient in. We want to see how you can contribute to our innovative solutions.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application directly and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at BlueCrest Capital Management
✨Know Your Cloud Platforms Inside Out
Make sure you brush up on your knowledge of Azure, AWS, and GCP. Be ready to discuss your hands-on experience with these platforms, especially in terms of deploying AI services and managing cloud security. Prepare specific examples of projects where you've designed or operated cloud environments.
✨Showcase Your AI Integration Skills
Be prepared to talk about your experience with AI platform operations. Highlight any instances where you've built or supported AI services in a public cloud environment. Discuss how you've integrated AI capabilities while ensuring compliance and governance, as this is crucial for the role.
✨Demonstrate Your Problem-Solving Abilities
Think of scenarios where you've had to balance operational support with engineering initiatives. Share examples that showcase your ability to troubleshoot issues in a fast-paced environment, particularly related to cloud platforms and AI services.
✨Communicate Clearly and Effectively
Since this role involves working with cross-functional teams, practice articulating your thoughts clearly. Be ready to explain complex technical concepts in simple terms, as you'll need to collaborate with various stakeholders, including those from non-technical backgrounds.