Senior Solutions Architect – AI

Job Description Senior Solutions Architect – AI Position Overview

The Senior Solutions Architect – AI will provide technical leadership for artificial intelligence and machine learning initiatives across the organization, directing multiple Agile teams focused on developing and deploying AI-powered solutions.

This individual will serve as a technical bridge between data science, engineering, enterprise architecture, shared services, product management, and business stakeholders. The Senior Solutions Architect will guide teams throughout the complete AI product lifecycle, from initial concept and proof of concept through production deployment, monitoring, and continuous improvement.

The ideal candidate brings extensive AI/ML architecture and product development experience, strong technical leadership capabilities, and a track record of delivering enterprise AI solutions that create measurable business value.

Lead the strategic direction of AI product development, including solution architecture, technical roadmaps, and implementation standards across multiple AI initiatives and platforms.

Maintain alignment with Principal Solution Architects, Enterprise Architecture, and supporting technology teams.

Guide the development of data pipelines, feature engineering processes, and model training workflows.

Establish and promote MLOps standards and best practices for model deployment, monitoring, maintenance, and continuous improvement.

Lead technical reviews focused on AI model performance, scalability, reliability, and business impact.

Establish metrics and KPIs to measure the effectiveness and value of AI initiatives.

Evaluate emerging AI technologies, methodologies, frameworks, and tools for potential enterprise adoption.

Develop AI solution approaches, model-selection strategies, system architectures, and deployment strategies.

Design and enable AI-powered solutions that enhance customer experiences and improve operational efficiency.

Support AI applications involving personalization, recommendation systems, inventory optimization, pricing, supply chain, and other enterprise operations.

Develop reusable AI components, frameworks, patterns, and services to accelerate future AI initiatives.

Develop proofs of concept (POCs) to validate potential AI applications before full-scale implementation.

Ensure AI architectures are scalable, secure, maintainable, and aligned with enterprise technology standards.

Provide technical direction and mentorship to multiple Agile teams consisting of Data Scientists, AI Engineers, Machine Learning Engineers, and Architects.

Foster a culture of technical excellence, innovation, collaboration, and continuous learning.

Guide teams through technical challenges involving model development, deployment, integration, and production support.

Promote AI-focused Agile development practices across delivery teams.

Serve as a key contributor within the Enterprise Architecture function.

Ensure AI initiatives comply with enterprise infrastructure, security, architecture, and data governance standards.

Collaborate with Enterprise Architects to establish and promote AI architecture principles, standards, and reusable patterns.

Influence the evolution of enterprise technology standards as AI capabilities continue to expand.

Participate in Architecture Review Boards and provide technical leadership for proposed AI initiatives.

Translate complex business requirements and challenges into scalable AI solution strategies and technical roadmaps.

Partner with AI Product Managers and business stakeholders to align AI initiatives with organizational priorities.

Develop measurement frameworks to evaluate the operational and financial impact of AI solutions.

Identify opportunities where AI and machine learning can improve customer experience, productivity, decision-making, and operational efficiency.

Ensure AI solutions comply with applicable privacy, security, governance, and ethical standards.

Partner with Responsible AI Governance teams to promote transparency, explainability, accountability, and ethical AI…