Job Summary
Serve as a Functional Architect within a global enterprise designing and optimizing solutions that integrate Generative AI API frameworks PL SQL and BlueYonder TMS for complex retail planning and transportation operations. Apply 10 to 12 years of experience to translate business requirements into scalable hybrid model architectures that improve efficiency reduce operational risk and enhance value delivery across the retail logistics ecosystem.
Responsibilities
Collaborate with business stakeholders to translate complex retail planning and transportation management objectives into functional architectures that align with enterprise standards and deliver measurable operational improvements
Design end to end solution workflows that integrate Generative AI capabilities with core BlueYonder transportation systems and supporting retail planning tools to enhance decision quality and automation across logistics processes
Define robust functional specifications for API integrations between BlueYonder transportation platforms and upstream and downstream retail applications to ensure accurate data exchange integrity and consistent process orchestration
Develop detailed PL SQL based functional data models and transformation logic to support transportation planning shipment execution and exception handling while maintaining high performance and reliability in hybrid environments
Evaluate current transportation and retail planning processes to identify functional gaps and propose innovative architecture enhancements that leverage Generative AI for demand forecasting routing optimization and performance analytics
Guide cross functional teams through requirement elaboration solution design walkthroughs and functional validation sessions to ensure that implemented features align with business goals and user experience expectations
Coordinate with technical architects and integration teams to ensure that functional designs for APIs PL SQL routines and BlueYonder configurations are feasible scalable and compatible with existing enterprise technology landscapes
Document comprehensive functional use cases process flows and configuration guidelines for BlueYonder transportation modules and related retail planning components to support consistent implementation and future maintainability
Support system testing cycles by defining functional test scenarios validating outcomes against transportation and retail planning business rules and driving timely resolution of defects to protect solution quality
Provide ongoing functional advisory support to operations teams on the optimal use of BlueYonder transportation and planning features including analytics driven insights that improve service levels and cost efficiency
Partner with data and analytics specialists to shape Generative AI driven capabilities that enhance shipment planning load consolidation and delivery performance in retail supply chains while maintaining ethical and responsible AI practices
Contribute to continuous improvement initiatives by analyzing functional performance metrics for transportation and planning processes and recommending targeted enhancements that improve sustainability and societal impact through reduced waste and optimized routes
Align architectural decisions with hybrid work model expectations by enabling effective remote collaboration through clear documentation structured governance and streamlined functional communication across distributed teams
Qualifications
Demonstrate proven expertise with Generative AI concepts and practical applications in supply chain and retail contexts including the ability to articulate how AI augmented workflows improve forecasting routing and operational decisions
Show strong proficiency in designing and validating API based integrations among transportation systems retail planning platforms and enterprise applications using standardized patterns and secure data handling practices
Apply advanced PL SQL skills to define logical data structures complex queries and performance optimized procedures that support high volume transportation and retail planning transactions
Exhibit deep functional knowledge of BlueYonder transportation management processes including planning tendering execution and settlement with a track record of successful implementations in large scale environments
Bring relevant experience in retail planning concepts such as demand planning allocation replenishment and promotion related impacts while effectively connecting these domains to transportation constraints and capabilities
Possess solid understanding of transportation management principles in retail networks including multimodal shipment strategies carrier collaboration and service level optimization to inform architecture decisions
Utilize clear and structured communication abilities to document functional requirements explain solution tradeoffs and guide diverse stakeholders through complex transportation and planning transformations
Apply problem solving and analytical skills to diagnose root causes of functional issues in integrated transportation and retail planning landscapes and recommend practical corrective actions
Demonstrate familiarity with hybrid work practices and collaboration tools to maintain productivity documentation quality and stakeholder engagement across onsite and remote settings
Maintain awareness of industry trends in retail logistics AI enabled planning and transportation optimization to keep architectures current and support the organization mission of more efficient and sustainable supply chains
Show experience in working within global matrix organizations where coordination prioritization and structured consultation lead to high quality outcomes without formal leadership responsibilities
Display commitment to quality compliance and ethical standards in designing and validating AI driven functionalities within transportation and retail planning solutions
Certifications Required
Preferred certifications include BlueYonder transportation management certification and Oracle PL SQL professional credential plus training in Generative AI or applied machine learning
