Solutions Architect

Job Title: Lead AI Business Solution Architect (Conversational AI & Chatbots) Experience: 13 + Year. Job Summary We are seeking an experienced and strategic Lead AI Business Solution Architect specializing in Conversational AI and Chatbot solutions . This role is responsible for designing and delivering scalable, AI-driven conversational ecosystems by bridging business needs with technology solutions. The ideal candidate will have strong expertise in multi-system integration architectures , enabling seamless connectivity between conversational platforms and enterprise applications. Key Responsibilities Strategic & Business Alignment Collaborate with business stakeholders to understand objectives, customer journeys, and operational needs. Translate business requirements into scalable conversational AI solutions aligned with enterprise goals. Define solution vision, roadmap, and measurable value outcomes. Solution Architecture & Design Design end-to-end architecture for chatbots, virtual assistants, and voice-based AI systems. Architect multi-channel conversational experiences (web, mobile, messaging platforms, IVR, etc.). Ensure scalability, resilience, and performance of AI solutions. Integration Architecture (Key Focus Area) Design and oversee complex multi-system integrations between conversational AI platforms and enterprise systems, including: CRM systems (Dynamics 365) Contact center platforms (Genesys, Methone) ERP and backend systems Knowledge bases and content management systems Third-party AI/ML and vendor platforms Define API-driven, event-driven, and microservices-based integration patterns . Ensure secure, reliable, and real-time data exchange across systems. Work on middleware and integration platforms (e.g., MuleSoft, Azure Integration Services, REST APIs). Address integration challenges such as latency, orchestration, data consistency, and fault tolerance. AI & Conversational Design Oversight Provide guidance on conversation design (intents, entities, dialog flows, automation). Apply best practices in NLP/NLU, LLMs, RAG, and prompt engineering . Ensure governance with AI guardrails, compliance, and ethical AI practices.