Solutions Architect - AI, Machine Learning & Enterprise Solutions

• Lead discovery workshops with executive stakeholders to understand business objectives, operational challenges, existing technology ecosystems, and future-state goals.
• Analyze current-state business processes and identify opportunities for AI, ML, conversational AI, automation, cloud modernization, and enterprise application improvements.
• Develop trusted client relationships and serve as a strategic technology advisor throughout the engagement lifecycle.

Solution Architecture

• Design enterprise technology solutions utilizing AI, ML, cloud technologies, CRM, ERP, APIs, and enterprise integrations.
• Architect customer-facing conversational AI solutions across voice/phone and SMS/text channels.
• Develop architectures that balance business objectives, user experience, scalability, security, reliability, and cost.
• Produce architecture diagrams, solution designs, technical roadmaps, implementation plans, and executive presentations., * Design and implement Artificial Intelligence and Machine Learning solutions.
• Implement Generative AI, Large Language Models (LLMs), RAG, prompt engineering, AI agents, intelligent automation, and predictive analytics.
• Design AI-powered customer engagement solutions with appropriate security, governance, monitoring, and scalability.

Enterprise Platforms

• CRM: Salesforce, Microsoft Dynamics 365, HubSpot, Oracle CX, ServiceNow, or comparable platforms.
• ERP: SAP, Oracle ERP/Fusion, Workday, Microsoft Dynamics 365, NetSuite, or comparable platforms.
• Integrations: REST APIs, SOAP APIs, GraphQL, microservices, MuleSoft, Dell Boomi, Azure Integration Services, event-driven architecture, webhooks, and middleware.
• Cloud: Microsoft Azure, AWS, and/or Google Cloud Platform.

Solution Delivery

• Partner with engineering teams throughout implementation to ensure solutions are delivered according to architectural standards.
• Participate in solution validation, testing, client demonstrations, production readiness reviews, UAT, change management, and adoption planning.
• Measure solution effectiveness and identify opportunities for continuous improvement.

Required Conversational AI & Customer Engagement Experience

• Hands-on experience designing, building, implementing, and deploying customer-facing AI agents capable of engaging customers through both phone/voice and SMS/text channels.
• Experience with real-time AI voice agents operating through telephone/telephony channels.
• Experience with AI agents capable of sending, receiving, and responding to customer SMS/text messages.
• Experience developing agents for use cases such as customer service, appointment scheduling, lead qualification, sales, intake, account servicing, technical support, or similar customer-facing workflows.
• Experience integrating conversational AI agents with CRM, ERP, scheduling, customer-service, contact-center, or other enterprise systems.
• Hands-on experience with one or more relevant technologies such as Twilio, Vapi, Retell AI, ElevenLabs, Deepgram, Amazon Connect, Amazon Lex, Google Dialogflow, Microsoft Copilot Studio, Genesys Cloud, NICE CXone, Five9, Cognigy, Kore.ai, or comparable platforms.
• Candidates must be able to describe the AI agents they personally designed, built, or implemented, including the client/organization, industry, business use case, technologies used for voice and text/SMS, and production outcome., * Bachelor’s degree in Computer Science, Information Technology, Engineering, Information Systems, Business Information Systems, or a related technical field.
• 5+ years of Solutions Architecture, Enterprise Architecture, Technology Consulting, or Digital Transformation experience.
• Demonstrated experience designing and implementing enterprise AI and ML solutions.
• Demonstrated hands-on experience deploying conversational AI agents across both voice/phone and SMS/text channels.
• Experience implementing or integrating CRM and ERP platforms.
• Experience designing enterprise API and integration architectures.
• Experience with enterprise cloud platforms including Azure, AWS, or GCP.
• Strong understanding of enterprise application architecture, security, scalability, governance, and production delivery.
• Excellent communication, presentation, client discovery, and executive stakeholder management skills.