AI Cloud Engineer
London (Hybrid): Onsite 4:1 WFH
Inside IR35 Contract
We're seeking a forward-thinking engineer ready to sit at the absolute intersection of Cloud Infrastructure and Artificial Intelligence within this international banking group. This is a unique opportunity to join a small, dynamic team within a leading financial services institution as they evolve their digital engineering capabilities. You will play a pivotal role in building the secure, scalable foundations that underpin critical banking services, transitioning from traditional cloud functions into a high-impact AI enablement powerhouse.
Key Responsibilities
* Design and implement cloud and AI-ready solutions on Azure, building repeatable patterns and integration services that support next‑generation workloads.
* Develop bespoke components using the OpenAI SDK and GPT models, ensuring all AI adoption is underpinned by robust governance and safety guardrails.
* Drive automation through Infrastructure-as-Code (Bicep, Terraform) and CI/CD pipelines, while maintaining REST APIs and identity‑aware solution patterns.
* Work autonomously to manage ambiguity, collaborating across infrastructure and application teams to enhance platform stability and cost efficiency.
Skills & Experience Required
* Azure expertise: Deep hands‑on experience with Azure engineering, PaaS services, and Infrastructure-as-Code (Bicep, ARM, or Terraform).
* Software engineering: Strong proficiency in Python (essential) and PowerShell for building automation frameworks, REST APIs, and identity flows (OAuth2).
* Identity & security: Solid understanding of Entra ID, IAM patterns, and implementing security controls within a regulated environment.
* AI integration: Familiarity with Azure OpenAI, embeddings, and vector workflows, with the ability to operationalise responsible AI controls.
* Qualifications: Hold an Azure certification (AZ‑104 or higher) and a Bachelor's degree or equivalent professional experience.
Desirables
* Experience with Azure API Management, AI orchestration frameworks, or knowledge of AI model lifecycle controls.
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