Azure AI Solution Engineer

Public Sector Resourcing•London Britain Township, PA
•Hybrid

About The Position

On behalf of the Cabinet Office Public Sector Fraud Authority, the Azure AI Solution Engineer will work on the Digital Fraud Fabrication (DFF) Project. This is a hands-on technical role focused on building, fine-tuning, and integrating advanced artificial intelligence and machine learning solutions in Microsoft Azure. The engineer will build and deploy production-grade AI pipelines, generative AI applications, and anomaly detection models to analyse documents for AI generation, manipulation, and fraud. The role is a six-month hybrid contract based in London, with attendance once every other week. It can only be worked within the UK and not overseas. The role is inside IR35 and falls within the scope of the Off Payroll Working in the Public Sector legislation.

Requirements

  • Deep hands-on experience with Azure OpenAI Service, Azure AI Search, Azure Foundry, Azure Cognitive Services (Document Intelligence), and Azure Databricks.
  • Fluency in Python and SQL.
  • Hands-on experience constructing enterprise RAG applications using LangChain, LlamaIndex, vector databases, and Azure AI Search.
  • Practical experience setting up MLflow, Azure DevOps, GitHub Actions, Docker, and Terraform or Bicep.

Nice To Haves

  • Practical experience applying AI to fraud detection, including tuning models for anomaly detection, graph network linkages, or financial crime patterns.
  • Working knowledge of GDS Service Standards, CDDO AI guidelines, and secure data handling under UK GDPR and Official Sensitive guidelines.
  • Active Security Check (SC) clearance or immediate eligibility.
  • Microsoft Certified: Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100).

Responsibilities

  • Build, fine-tune, and integrate AI and machine learning solutions in Microsoft Azure.
  • Build and deploy production-grade AI pipelines and generative AI applications.
  • Develop anomaly detection models to analyse documents for AI generation, manipulation, and fraud.
  • Construct enterprise retrieval-augmented generation (RAG) applications.
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