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Azure Platform Engineer - Azure ML Studio / Terraform / Data Engineering

Hybrid- majority remote

Contract

Overview:

We are seeking an experienced Azure Platform Engineer with a strong background in Azure Machine Learning (ML) Studio, Infrastructure as Code (Terraform), and Data Engineering. You will play a key role in designing, building, and maintaining cloud-based data and ML platforms to support large-scale analytics and AI initiatives.

Key Responsibilities:Design, implement, and manage Azure cloud infrastructure to support ML and data workloads.Develop and maintain Terraform scripts for infrastructure automation and environment provisioning.Collaborate with data scientists and engineers to deploy and operationalize ML models using Azure ML Studio.Build and optimize data pipelines leveraging Azure Data Factory, Data Lake, Synapse, and related tools.Ensure scalability, security, and reliability across data and ML environments.Support CI/CD integration, monitoring, and continuous improvement of Azure resources.Essential Skills & Experience:Proven experience as an Azure Platform Engineer / Cloud Engineer / DevOps Engineer.Strong hands-on experience with Azure ML Studio and ML model deployment.Solid understanding of Terraform and Infrastructure as Code (IaC)Experience with Azure Data Services - Data Factory, Synapse, Data Lake, Databricks.Good scripting knowledge (Python, PowerShell, or Bash).Familiarity with CI/CD pipelines using Azure DevOps or GitHub Actions.Strong communication and problem-solving skills.

GCS is acting as an Employment Business in relation to this vacancy.

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GenAI Enterprise Architect - Microsoft Copilot Studio & Azure

Start Date: ASAP

Contract - Hybrid- Mostly remote

We're working with a major UK utilities provider undergoing a digital transformation to embed Generative AI into its operational and customer-facing processes. They are seeking a seasoned GenAI Solution Architect to lead the delivery of an AI-powered automation solution using Microsoft Copilot Studio, backed by Azure services.

This is a high-profile contract focused on improving scalability, reducing operational workload, and accelerating response times in a regulated, high-volume environment.

Key Responsibilities

Lead the delivery of a production-grade GenAI solution in Microsoft Copilot Studio to automate complex, document-based reporting workflows.Transition from an Azure OpenAI proof of concept to a fully integrated solution across Azure cloud services (e.g., Azure Functions, Logic Apps, Blob Storage).Resolve platform limitations and manage technical escalations through Microsoft engineering teams-including GPU resource management and service configurations.Design safe, reliable, and predictable AI outputs through prompt architecture and LLM constraint tuning.Support integration with existing enterprise systems, retrieval pipelines, and data sources-ensuring performance, compliance, and security.Enable internal teams through documentation, knowledge transfer, and hands-on support.Proven track record designing and delivering AI/GenAI solutions in a production environment-experience with Microsoft Copilot Studio is essential.Deep knowledge of the Azure ecosystem, including AI and integration services.Strong hands-on skills in prompt engineering, LLM governance, and AI system debugging.Experience in regulated sectors (ideally energy, utilities) with a focus on security, resilience, and scalability.Excellent stakeholder management skills and ability to work under pressure in high-impact programmes.

Please send across an updated CV if this position is of interest

GCS is acting as an Employment Business in relation to this vacancy.

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GenAI Solution Architect - Microsoft Copilot Studio & Azure

Start Date: ASAP

Contract - Hybrid- Mostly remote

We're working with a major UK utilities provider undergoing a digital transformation to embed Generative AI into its operational and customer-facing processes. They are seeking a seasoned GenAI Solution Architect to lead the delivery of an AI-powered automation solution using Microsoft Copilot Studio, backed by Azure services.

This is a high-profile contract focused on improving scalability, reducing operational workload, and accelerating response times in a regulated, high-volume environment.

Key Responsibilities

Lead the delivery of a production-grade GenAI solution in Microsoft Copilot Studio to automate complex, document-based reporting workflows.Transition from an Azure OpenAI proof of concept to a fully integrated solution across Azure cloud services (e.g., Azure Functions, Logic Apps, Blob Storage).Resolve platform limitations and manage technical escalations through Microsoft engineering teams-including GPU resource management and service configurations.Design safe, reliable, and predictable AI outputs through prompt architecture and LLM constraint tuning.Support integration with existing enterprise systems, retrieval pipelines, and data sources-ensuring performance, compliance, and security.Enable internal teams through documentation, knowledge transfer, and hands-on support.Proven track record designing and delivering AI/GenAI solutions in a production environment-experience with Microsoft Copilot Studio is essential.Deep knowledge of the Azure ecosystem, including AI and integration services.Strong hands-on skills in prompt engineering, LLM governance, and AI system debugging.Experience in regulated sectors (ideally energy, utilities) with a focus on security, resilience, and scalability.Excellent stakeholder management skills and ability to work under pressure in high-impact programmes.

Please send across an updated CV if this position is of interest

GCS is acting as an Employment Business in relation to this vacancy.

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Azure Platform Engineer -AI/ML

This position is 90% remote

We're looking for a highly skilled Azure Platform Engineer with a strong background in Artificial Intelligence (AI) and Machine Learning (ML) to support a key enterprise project. This role is focused on deploying and optimising AI/ML workloads on Azure, and will involve working closely with our engineering and data science teams to ensure our platform is robust, secure, and scalable.

This is a hands-on engineering role that requires a deep understanding of the Azure ecosystem, especially how it's tailored in enterprise environments.

Key skills

Design, build and manage scalable Azure environments for AI/ML solutionsSupport deployment of custom AI models using Azure Machine Learning and related servicesCollaborate with data scientists and ML engineers to productionise AI workloadsStrong expertise with Azure services (Azure ML, Azure Kubernetes Service, Azure Data Lake, Synapse, etc.)Experience in enterprise Azure environments, including common customisations (e.g. private networking, policy, RBAC)Strong understanding of cloud infrastructure, DevOps practices, and CI/CD pipelinesProficiency with IaC tools - Bicep, ARM, or TerraformFamiliarity with security and compliance requirements in enterprise settingsCustomise Azure platform components to align with enterprise security, networking, and compliance requirementsOptimise infrastructure for performance and cost efficiencyDevelop and maintain Infrastructure as Code (IaC) using tools like Bicep, ARM templates, or TerraformTroubleshoot and resolve complex platform and deployment issuesProven experience deploying AI/ML solutions on Azure

Please send across an updated CV if this position is of interest

GCS is acting as an Employment Business in relation to this vacancy.

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