AI/ML Engineer

Job Summary

Responsibilities

• Design adaptive experience strategies that integrate concepts of large language models and generative AI to deliver highly contextual and personalized journeys across digital touchpoints for global retail vendor ecosystems.
• Develop detailed interaction flows and service blueprints that translate complex AI and ML capabilities into intuitive experiences that enhance vendor productivity and operational transparency.
• Create prototypes and experience artifacts that demonstrate how generative AI platform architecture can be used by vendor management stakeholders to make faster and more informed decisions.
• Collaborate with data science teams to define user centric data models and experimentation plans that ensure recommendations and insights are explainable and trustworthy for business and vendor partners.
• Align adaptive experiences with enterprise AI platform architecture by specifying experience layer requirements that support scalability reuse observability and responsible AI practices.
• Analyze qualitative and quantitative user data to refine experience concepts and measure the impact of AI powered features on vendor satisfaction process efficiency and retail supply chain performance.
• Define clear problem statements and success metrics for each AI driven experience initiative and maintain traceability between business outcomes user needs and technical implementation choices.
• Facilitate discovery sessions and design workshops with product engineering and operations stakeholders to uncover use cases where generative AI and data science can meaningfully improve vendor management processes.
• Document experience patterns content guidelines and conversational flows that guide how adaptive interfaces should respond across different scenarios while maintaining compliance and ethical standards.
• Partner with product managers to build roadmaps where experiential milestones are explicitly linked to data readiness AI model maturity and platform architecture evolution.
• Review and refine ML powered features before release by validating that stimuli responses and feedback loops align with defined experience principles and reduce friction for users.
• Coordinate with retail vendor management specialists to ensure that adaptive experiences respect industry practices contractual constraints and operational realities in a hybrid work setting.
• Champion inclusive and accessible design by ensuring that AI driven interactions accommodate diverse user preferences and reduce cognitive load for vendor and internal stakeholders.

Qualifications

• Apply deep knowledge of concepts of large language models to design experiences that harness generative capabilities in controlled and purposeful ways aligned to enterprise objectives.
• Use understanding of generative AI platform architecture to collaborate effectively with engineers on topics such as orchestration observability safety controls and integration with retail systems.
• Demonstrate strong grounding in AI and ML concepts including supervised and unsupervised learning model evaluation and feedback loops to inform experience design decisions.
• Leverage data science expertise to interpret analytical outputs define relevant metrics and design user journeys that promote continuous learning and model improvement.
• Draw on vendor management retail exposure to craft workflows and information architectures that reflect typical vendor lifecycles performance evaluations and dispute resolution processes.
• Communicate complex technical ideas in simple and actionable terms to multidisciplinary teams enabling shared understanding of how adaptive experiences will be implemented and measured.
• Operate effectively in a hybrid work model using digital collaboration tools to co create artifacts document decisions and maintain alignment across geographically distributed stakeholders.
• Maintain strong attention to detail and structured thinking developed over ten to fourteen years of professional experience in experience design AI enabled solutions or related fields.