Pega Lead Decisioning Architect

Job Requirements • Lead the architecture and implementation of Pega Customer Decision Hub and customer decisioning solutions. • Design and implement Next-Best-Action (NBA) strategies, decision strategies, engagement policies, and arbitration rules. • Define and optimize decisioning frameworks using Pega CDH, predictive models, adaptive models, and real-time customer insights. • Translate business requirements into scalable, reusable, and high-performance technical solutions. • Lead solution design, technical reviews, coding standards, and architecture governance. • Collaborate with business, product, data science, integration, and engineering teams to align decisioning solutions with business objectives. • Oversee integrations with CRM platforms, customer data platforms, APIs, and enterprise applications. • Troubleshoot performance issues, optimize decisioning execution, and ensure scalability and reliability. • Mentor developers and decisioning engineers, and provide technical leadership throughout the delivery lifecycle. • Ensure compliance with enterprise architecture standards, security policies, and regulatory requirements. Required Skills And Qualifications • 8+ years of overall IT experience, with substantial experience in Pega implementation and decisioning architecture. • Strong hands-on experience with Pega Customer Decision Hub (CDH) and Next-Best-Action (NBA) framework. • Expertise in decision strategies, arbitration, engagement policies, actions, treatments, propositions, and contact policies. • Strong understanding of Adaptive Decision Manager (ADM), predictive models, adaptive models, customer segmentation, and Interaction History. • Experience designing real-time and batch decisioning solutions across inbound and outbound channels. • Strong knowledge of Pega architecture, performance tuning, integration patterns, and enterprise solution design. • Experience with REST/SOAP APIs, SQL, JSON/XML, and enterprise system integrations. • Proven experience leading technical teams, conducting design reviews, and engaging with senior business and IT stakeholders. • Strong communication, analytical, problem-solving, and stakeholder-management skills. Preferred Certifications • Pega Certified Lead Decisioning Architect (PCDLDA). • Pega Certified Decisioning Consultant (PCDC/CPDC, depending on certification version). • Pega Certified Lead System Architect (PCLSA/CLSA), preferred." Work Experience 7-10Years

8+ years of overall IT experience, with substantial experience in Pega implementation and decisioning architecture. Strong hands-on experience with Pega Customer Decision Hub (CDH) and Next-Best-Action (NBA) framework. Expertise in decision strategies, arbitration, engagement policies, actions, treatments, propositions, and contact policies. Strong understanding of Adaptive Decision Manager (ADM), predictive models, adaptive models, customer segmentation, and Interaction History. Experience designing real-time and batch decisioning solutions across inbound and outbound channels. Strong knowledge of Pega architecture, performance tuning, integration patterns, and enterprise solution design. Experience with REST/SOAP APIs, SQL, JSON/XML, and enterprise system integrations. Proven experience leading technical teams, conducting design reviews, and engaging with senior business and IT stakeholders. Strong communication, analytical, problem-solving, and stakeholder-management skills.

Lead the architecture and implementation of Pega Customer Decision Hub and customer decisioning solutions. Design and implement Next-Best-Action (NBA) strategies, decision strategies, engagement policies, and arbitration rules. Define and optimize decisioning frameworks using Pega CDH, predictive models, adaptive models, and real-time customer insights. Translate business requirements into scalable, reusable, and high-performance technical solutions. Lead solution design, technical reviews, coding standards, and architecture governance. Collaborate with business, product, data science, integration, and engineering teams to align decisioning solutions with business objectives. Oversee integrations with CRM platforms, customer data platforms, APIs, and enterprise applications. Troubleshoot performance issues, optimize decisioning execution, and ensure scalability and reliability. Mentor developers and decisioning engineers, and provide technical leadership throughout the delivery lifecycle. Ensure compliance with enterprise architecture standards, security policies, and regulatory requirements.