Microsoft Power Platform

7 days ago

London, Greater London, United Kingdom Jobs via eFinancialCareers Full time £100,000 - £120,000 per year

Microsoft Power Platform / Agentic AI Engineer
City of London
Hybrid (3/2 split)
6-months contract
£705 per day (via Umbrella)
cer Financial are working alongside an international bank who are based in the City of London. They are seeking a Microsoft Power Platform / Agentic AI Engineer to work with them on a contract.

The responsibilities of a Microsoft Power Platform / Agentic AI Engineer will include:

  • Design and build conversational agents using Microsoft Copilot Studio.
  • Develop Power Automate flows triggered by AI agents or business events.
  • Create Power Apps frontends integrated with GenAI services and enterprise data.
  • Build and manage custom connectors to internal APIs and third-party services.
  • Microsoft 365 & Graph API Integration
  • Enable agents to access and reason over content in: SharePoint, OneDrive, Teams, Outlook, and Planner

Architect multi-step agent workflows using:

  • Semantic Kernel SDK (C# or Python)
  • Azure OpenAI (GPT-4, function calling, chat completion)
  • Planner and Kernel Memory APIs for reasoning and memory
  • RAG pipelines grounded in enterprise data via Azure AI Search

Enterprise Data & AI Services Integration:

  • Azure AI Search (vector indexing, hybrid search)
  • Azure Form Recognizer for document understanding
  • Azure Language Services for summarization, translation, and NER

Deploy solutions using:

  • Azure Kubernetes Service (AKS) or Azure Container Apps
  • Azure Key Vault, Monitor, and RBAC
  • Microsoft Entra ID (Azure AD) for identity and access control

The successful Microsoft Power Platform / Agentic AI Engineer will have experience in:

  • Copilot Studio, Power Automate, Power Apps, custom connectors
  • SharePoint Development
  • Proficiency in Microsoft Graph API, Azure OpenAI, and Semantic Kernel
  • Solid programming skills in Python and/or C#
  • LangChain, AutoGen, or similar orchestration frameworks
  • Azure AI Search, Form Recognizer, and Language Services
  • GitHub Actions, CI/CD, and DevSecOps practices
  • Responsible AI frameworks (e.g., NIST AI RMF, ISO/IEC 42001)
  • GDPR, data residency, and DLP policies
  • Azure DevOps, ARM/Bicep, or Terraform
  • Proven track record delivering agent-based or GenAI solutions in enterprise or regulated environments

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