Sr. Solutions Architect AI- Remote

The Sr Solution Architect AI helps to lead artificial intelligence and machine learning initiatives, directing multiple Agile PODs focused on developing AI-powered solutions. This role serves as the technical bridge between data science, engineering, shared services, and product management to deliver transformative AI products. The Sr Solution Architect is responsible for guiding delivery teams through the complete AI product development lifecycle from conception to deployment and continuous improvement. They will drive innovation in personalization technologies, operational efficiency, and customer experience enhancements while establishing best practices for AI development, implementation and operation., Lead the strategic direction for AI product development, including solution architecture, technical roadmaps, and implementation standards across multiple AI initiatives and platforms. Maintaining alignment with the Principal Solution Architect and supporting groups/teams. Support and guide the development of data pipelines, feature engineering, and model training workflows. Guide teams in implementing MLOps practices for model deployment, monitoring, and maintenance help contribute towards standards and best practices Lead and facilitate technical reviews and provide guidance on AI model performance, scalability, and business impact Establish metrics and KPIs to measure the effectiveness of AI initiatives Stay current with emerging AI technologies and methodologies, evaluating their potential application

Technical Design: Exercise independent judgment in developing AI solution approaches, model selection, and deployment strategies. Enable the design and implementation of AI-powered solutions for enhancing the customer shopping experience, drive operational efficiency across the enterprise, optimizes inventory, pricing, supply chain, and other operations Drive the development of reusable AI components and frameworks to accelerate future initiatives Develop POCs (proof of concepts) to validate AI applications before full-scale implementation

Team Support: Direct and mentor multiple Agile teams comprising data scientists, AI engineers, and ML specialists, fostering a culture of innovation, learning, and excellence in AI development.

Enterprise Coordination: As part of the Enterprise Architecture (EA) team, ensure AI initiatives comply with corporate infrastructure, security, and data governance standards while influencing the evolution of those standards. Collaborate with fellow Enterprise Architects to proliferate AI principles and patterns.

Strategy: Translate business requirements into technical AI roadmaps, working with AI Product Manager and business stakeholders to align AI initiatives with organizational goals while establishing measurement frameworks to track impact.

Governance: Participate and provide thought leadership in Architecture Review Board and review AI initiatives Ensure AI solutions adhere to privacy, security, and ethical standards

Cultural Champion: Drive the adoption of AI-focused agile development practices, and partner with Responsible AI Governance team to promote transparency, explainability and ethical use of AI.

Product Management: Partner with the Product Management Organization to identify opportunities for AI implementation, build consensus around AI priorities, and communicate complex technical concepts to non-technical stakeholders Partner with Product Owners to translate business requirements into AI-specific technical requirements

Master’s degree in Computer Science, Data Science, AI/ML, or equivalent professional experience 10+ years of experience in AI/ML product development or related technical fields 4+ years of experience leading teams of data scientists, AI engineers or architects Demonstrated success leading AI initiatives in personalization, recommendation systems, computer vision, or operational efficiency In-depth knowledge of machine learning algorithms, frameworks, and best practices Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, etc.) and cloud-based AI services Proven experience with agile methodologies in the context of AI/ML Strong experience managing the full AI product lifecycle Track record of implementing successful AI solutions that delivered measurable value Experience with MLOps practices and tools for model deployment and monitoring Demonstrated ability to translate complex business problems into AI solution approaches Excellent communication skills with ability to explain AI concepts to both technical and non-technical audiences Experience in retail or e-commerce preferred Familiarity with AI governance, ethics, and responsible AI implementation Ability to work effectively in an onshore/offshore development model Travel required per the company policy