AI Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Design, develop, and implement AI agents that address customer and business challenges.

• Convert product requirements and use cases into scalable, production-ready solutions.

• Construct and manage MCP servers that ensure secure access to tools, systems, and enterprise data.

• Establish tool interfaces, authentication protocols, and resource access patterns.

• Integrate agents with Microsoft Dynamics 365, Microsoft Graph, Dataverse, ServiceNow, customer experience platforms, and both internal and external APIs.

• Outline strategies for memory, context, decision-making, retrieval, reasoning, and tool utilization.

• Create guardrails for the safe and effective operation of enterprise agents.

• Develop adapters, event-processing capabilities, and integration layers.

• Enable agents to exchange insights within an interconnected intelligence ecosystem.

• Collaborate with Product, Engineering, QA, and AI leadership teams.

• Provide technical expertise, customer insights, and market observations to inform the Agent Factory roadmap and backlog.

• Uphold information security by adhering to policies, safeguarding data, securely utilizing systems, reporting incidents, completing necessary training, and managing confidential information securely.

⛳️ Requirements

• Extensive software engineering experience with C# and .NET.

• Practical experience with Azure services, including Azure Functions, Azure App Service, Azure OpenAI Service, and Azure AI Foundry / AI Studio.

• Experience in integrating with Dynamics 365, Dataverse, Microsoft Graph, or Power Platform.

• Familiarity with Azure security and identity services, such as Microsoft Entra ID, Managed Identities, and Azure Key Vault.

• Hands-on experience in building or utilizing MCP servers.

• Knowledge of Semantic Kernel, AutoGen, or Microsoft AI SDKs.

• Experience with function and tool invocation, RAG, vector databases, and context and memory management.

• Strong background in API integration, including REST APIs, webhooks, and event-driven architectures.

• Experience with cloud-native deployment, CI/CD pipelines, and infrastructure-as-code methodologies.

• Understanding of performance, latency, reliability, and cost considerations for production LLMs.

• Dedication to software quality, testing, and continuous improvement.

• Ability to collaborate closely with QA teams on agent evaluation, testing, and quality assurance.

• Experience with multi-agent architectures, regulated environments, LLM observability, customer experience platforms, or enterprise workflow automation is a plus.

🏝️ Benefits

• No specific benefits, perks, or compensation extras are mentioned in the posting.