AI Solutions Architect - CRM & AI Integration

• 15+ years of overall IT experience, with strong CRM platform expertise.
• Hands-on experience with Microsoft Dynamics 365 (preferred).
• Proven track record architecting and deploying AI/ML solutions in enterprise applications.
• (If Dynamics 365 not present) Demonstrated Sales AI experience — conversation intelligence, predictive scoring, forecasting tools.
• Strong knowledge of enterprise data architecture, integration patterns, and governance.
• Excellent communication and stakeholder management skills.

• Microsoft certifications (Dynamics 365, Azure AI Engineer, Power Platform).
• Hands-on with Microsoft’s AI stack: Copilot Studio, Azure OpenAI Service, Power Platform AI Builder, Dataverse.
• Familiarity with enterprise architecture frameworks (e.g., TOGAF).
• Experience with Power Automate and low-code/no-code orchestration tools.
• Background in sales or customer service operations.

Must-have skills

CRM Integration, Microsoft Dynamics 365

Good-to-have skills

AI/ML, solution architect

• →Partner with business stakeholders to translate strategic goals into CRM + AI architecture.
• →Act as the primary technical liaison with Microsoft, aligning on platform capabilities and roadmap.
• →Collaborate with enterprise architecture teams to ensure compliance with standards, security, and integration patterns.
• →Design and oversee delivery of AI-driven CRM capabilities, including:
• →AI-powered lead scoring and prioritization.
• →Conversational AI / Copilot integrations.
• →Generative AI for customer insights (Azure OpenAI Service).
• →Intelligent sales forecasting (Azure Machine Learning pipelines).
• →Next-best-action recommendations for sales/service reps.
• →Customer 360 / unified data architecture across Dynamics 365, Power Platform, Dataverse, and external systems.
• →AI-assisted customer service (case routing, sentiment detection, resolution suggestions).
• →Agentic workflows orchestrated via Dynamics 365, Power Automate, and Azure AI services.
• →Define architecture patterns, data flows, and governance standards for secure, scalable AI solutions.
• →Lead technical design sessions and produce clear architecture documentation.
• →Evaluate build-vs-buy trade-offs between native CRM AI features and custom AI/ML development.
• →Guide implementation teams through delivery, testing, and rollout.