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# AI Platform Engineer

- **Company:** Portfolio Group Ltd
- **Location:** London, UK
- **Salary:** £80,000.0 - £100,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Cloud Engineering, DevOps, Github, Python (Programming Language), Search Technologies, Large Language Models, Generative AI, AI Platforms, Infrastructure Automation Frameworks, Terraform, Microservices
- **Published:** September 19, 2026
- **Apply:** https://www.reed.co.uk/jobs/ai-platform-engineer/57363467

## About the Role

* Experience designing and supporting cloud platforms on Microsoft Azure.
 * Strong Terraform and Infrastructure-as-Code experience.
 * Experience with containerised applications and CI/CD pipelines.
 * Python for automation and scripting.
 * A good understanding of cloud-native architecture, APIs and microservices.
 * Experience with vector search technologies such as OpenSearch would be advantageous.
 * Experience with Microsoft Foundry or Azure AI Foundry is desirable but not essential. We're equally interested in experienced Azure Platform, Cloud or DevOps Engineers looking to build their expertise in enterprise AI.

## Description

We're looking for an experienced AI Platform Engineer to help build and evolve the Azure platform that powers our conversational AI products and wider AI strategy.You'll design, build and operate the cloud-native platform supporting Retrieval-Augmented Generation (RAG), LLM orchestration, vector search and production AI services, working closely with AI Engineering, DevOps and Security teams to deliver scalable, secure and reliable AI solutions.

Role scope:

 * Designing, building and operating AI platform infrastructure across Microsoft Azure.
 * Developing and optimising RAG pipelines, AI services and platform components.
 * Deploying infrastructure using Terraform and supporting containerised applications.
 * Building and maintaining CI/CD pipelines using GitHub and Azure DevOps.
 * Improving observability, monitoring and platform resilience.
 * Supporting vector search, embedding pipelines and knowledge ingestion.
 * Applying security and governance best practice across the AI platform.


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