Microsoft Dynamics 365 CRM & AI Solutions Architect

Everware Consulting GmbH•Philadelphia, PA

14h

About The Position

We are looking for an experienced Microsoft Dynamics 365 CRM & AI Solutions Architect to lead the design and delivery of enterprise-grade CRM solutions, combining Microsoft Dynamics 365, Power Platform, Azure technologies, and emerging AI capabilities. The role defines end-to-end technical architectures, guides development teams, and translates business requirements into scalable, secure, and maintainable solutions. A key focus is integrating intelligent automation and agentic AI into CRM environments to enhance customer engagement, streamline operations, and deliver measurable business value. The architect leads Dynamics 365 Customer Engagement and Power Platform implementations and customisations, enterprise integrations, data migration, performance optimisation, environment management, and deployment strategies. They establish architecture governance, security practices, development standards, and application lifecycle management processes while coaching technical teams. The role also defines AI architecture and implementation strategies, including intelligent agents, agentic and multi-agent patterns, knowledge grounding, and AI-enabled CRM workflows. It leads proof-of-concept initiatives and supports the transition of successful AI solutions into secure, production-ready enterprise deployments, with governance for responsible AI, monitoring, lifecycle management, and operational controls.

Requirements

Strong hands-on experience with Microsoft Dynamics 365 Customer Engagement (CRM).
Extensive knowledge of Microsoft Dataverse and the Power Platform ecosystem.
Proficiency in C#, .NET Framework/.NET Core, JavaScript, and TypeScript.
Experience developing and extending plugins, custom workflows, custom APIs, and other Dynamics 365 components.
Solid understanding of CRM functional processes, particularly Sales, Customer Service, case management, and marketing-related capabilities.
Experience with solution management, application lifecycle management (ALM), and CI/CD pipelines using Azure DevOps.
Experience designing enterprise integrations using Azure Integration Services.
Strong understanding of REST APIs, web services, and Dataverse APIs.
Practical knowledge of Azure Functions, Logic Apps, Service Bus, and custom connectors.
Experience with enterprise data integration, migration, security, and performance optimisation.
Knowledge of the Microsoft AI ecosystem, including Dynamics 365 Copilot, Microsoft 365 Copilot, Copilot Studio, Azure OpenAI, Azure AI Foundry, AI Builder, and Power Platform Copilot capabilities.
Experience designing AI agents, agent orchestration patterns, and human-in-the-loop workflows.
Understanding of LLMs, prompt engineering, function calling, tool integration, and context management.
Experience implementing AI-driven CRM capabilities and intelligent business process automation.
Knowledge of RAG, Azure AI Search, vector search, semantic search, and enterprise knowledge grounding.
Understanding of AI governance, responsible AI principles, security, monitoring, and agent lifecycle management.
Strong architectural leadership and ability to guide multidisciplinary technical teams.
Excellent analytical, problem-solving, and strategic decision-making skills.
Ability to communicate complex technical concepts clearly to business stakeholders and senior management.
Experience collaborating across business, functional, and technical teams.
A proactive approach to innovation, continuous improvement, and emerging technologies.
Strong ownership of architecture quality, delivery standards, governance, and technical outcomes.

Responsibilities

Design and oversee end-to-end architectures for Microsoft Dynamics 365 Customer Engagement and Power Platform solutions.
Translate business objectives and functional requirements into technical designs aligned with enterprise architecture standards.
Guide developers and technical consultants; review solution designs, customisations, integrations, and code quality.
Lead integrations between Dynamics 365 and external enterprise applications using Azure services, APIs, and middleware.
Establish development standards, architecture governance, security practices, and application lifecycle management processes.
Oversee data migration, performance optimisation, environment management, and deployment strategies.
Identify architectural risks and dependencies, define mitigation plans, and support delivery across the project lifecycle.
Coach technical teams and promote best practices across Dynamics 365, Power Platform, cloud integration, and AI-enabled solutions.
Lead implementation and customisation of Dynamics 365 Customer Engagement solutions.
Design solutions using Microsoft Dataverse, Power Apps, Power Automate, and Power BI.
Define approaches for platform extensions through plugins, custom workflows, custom APIs, and client-side scripting.
Drive solution management, source control, automated testing, and CI/CD pipelines using Azure DevOps.
Define architecture and implementation strategies for AI-powered CRM and business process solutions.
Design and implement intelligent agents using Microsoft Copilot Studio, Dynamics 365 Copilot capabilities, and Azure AI technologies.
Develop agentic AI architectures incorporating autonomous and multi-agent patterns, orchestration, tool integration, and human oversight.
Identify opportunities to embed AI into customer service, sales, knowledge management, and operational workflows.
Lead AI proof-of-concept initiatives and guide successful solutions into secure, production-ready enterprise deployments.
Establish governance for AI security, responsible AI, monitoring, lifecycle management, and operational controls.
Support teams in prompt engineering, agent design, and adopting emerging AI capabilities.
Define and measure business outcomes such as reduced manual effort, faster case resolution, improved customer experience, and increased productivity.
Design AI-enabled CRM capabilities such as case summarisation, intelligent lead qualification, sentiment analysis, knowledge discovery, and next-best-action recommendations.
Apply LLMs, prompt engineering, function calling, and context management to enterprise use cases.
Architect knowledge-grounding solutions using RAG, Azure AI Search, semantic search, and vector-based retrieval.
Integrate AI agents and CRM processes with enterprise data sources, APIs, and business applications.
Design automation and integration patterns using Azure Functions, Logic Apps, Service Bus, custom connectors, and Power Automate.
Ensure AI-generated outputs and automated actions are governed, monitored, and aligned with business requirements.