AI Engineer

AnywhereNow

. Design, build, and deploy AI agents that solve customer and business problems .

Posted 11/1/2026full-timeRemote • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying AI agents, integrating with Microsoft technologies, and ensuring secure access to enterprise data. Proficient in software engineering with a focus on C#, .NET, and Azure services, while maintaining a commitment to software quality and continuous improvement.

Highest-signal resume keywords

C# ProgrammingAzure ServicesMicrosoft Dynamics 365 IntegrationAPI IntegrationCloud-Native Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringC#Azure FunctionsAzure App ServiceAzure OpenAI ServiceAPI IntegrationREST APIsInfrastructure-as-CodeMulti-Agent ArchitecturesContinuous Improvement

Soft Skills

CollaborationCustomer InsightsTechnical Expertise

Tools & Technologies

Microsoft GraphDataverseServiceNowMCP ServersSemantic KernelAutoGenMicrosoft AI SDKsEvent-Driven ArchitecturesCI/CD PipelinesAzure Key Vault

Industry Keywords

Enterprise Data SecurityContact Centre PlatformsCustomer Experience PlatformsRegulated EnvironmentsLLM Observability

Tech Stack

Tools & technologies

AzureCloudServiceNowVault.NET

About the role

Key responsibilities & impact

Design, build, and deploy AI agents that solve customer and business problems
Translate product requirements and use cases into scalable, production-ready solutions
Build and operate MCP servers providing secure access to tools, systems, and enterprise data
Define tool interfaces, authentication mechanisms, and resource access patterns
Integrate agents with Microsoft Dynamics 365, Microsoft Graph, Dataverse, ServiceNow, contact centre/customer experience platforms, and internal or third-party APIs
Define memory, context, decision-making, retrieval, reasoning, and tool-use strategies
Design guardrails for safe and effective enterprise agent operation
Develop adapters, event-processing capabilities, and integration layers
Enable agents to share insights across an interconnected intelligence ecosystem
Collaborate with Product, Engineering, QA, and AI leadership
Contribute technical expertise, customer insights, and market observations to the Agent Factory roadmap and backlog
Support information security by following policies, protecting data, securely using systems, reporting incidents, completing required training, and handling confidential information securely

Requirements

What you’ll need

Strong software engineering experience using C# and .NET
Hands-on experience with Azure services, including Azure Functions, Azure App Service, Azure OpenAI Service, and Azure AI Foundry / AI Studio
Experience integrating with Dynamics 365, Dataverse, Microsoft Graph, or Power Platform
Knowledge of Azure security and identity services, including Microsoft Entra ID, Managed Identities, and Azure Key Vault
Practical experience building or consuming MCP servers
Knowledge of Semantic Kernel, AutoGen, or Microsoft AI SDKs
Experience with function and tool calling, RAG, vector databases, and context and memory management
Strong API integration experience, including REST APIs, webhooks, and event-driven architectures
Experience with cloud-native deployment, CI/CD pipelines, and infrastructure-as-code approaches
Understanding of performance, latency, reliability, and cost considerations for production LLMs
Commitment to software quality, testing, and continuous improvement
Ability to work closely with QA teams on agent evaluation, testing, and quality assurance
Experience with multi-agent architectures, regulated environments, LLM observability, contact centre/customer experience platforms, or enterprise workflow automation is nice to have

Benefits

Comp & perks

No specific benefits, perks, or compensation extras are stated in the posting