Solution Architect Senior - AI​/ML Architecture

Position Overview

Position Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Solution Architect Senior within PNC’s Technology organization, you will be based in Pittsburgh, PA;
Cleveland, OH;
Birmingham, AL;
Dallas, TX or Denver, CO. This senior-level position is responsible for Strategy, Architecture, and Innovation spanning business, application, platform, data, and AI/ML domains.

• Develop solution, data, and AI/ML architecture and resolve complex issues across a variety of initiatives through requirements analysis, architectural leadership, and project supervision.
• Design solution architecture for large or complex programs, including system, application, data, and AI service designs, in alignment with enterprise strategies, standards, and target state roadmaps.
• Define and govern data architecture patterns, including logical and physical data models, canonical data structures, data domains, and master/reference data strategies, ensuring they support AI-ready data.
• Provide architectural leadership for data platforms and ecosystems, including data warehousing, data lakes/lake houses, analytical platforms, streaming architectures, and cloud‑based data services—enabling AI/ML platforms.
• Establish and enforce best practices for data modeling, integration, quality, metadata management, lineage, and lifecycle management, including support for model governance and auditability.
• Partner with business, analytics, and engineering teams to ensure architectures support reporting, analytics, AI/ML and GenAI, regulatory, and operational use cases, including defining reference architectures and reusable patterns.
• Provide consulting and guidance to IT, data engineering, and AI/ML engineering teams on data design, integration patterns, storage technologies, ML Ops practices, and architectural tradeoffs, including agentic coding workflows.
• Define reference architectures, patterns, and guardrails for agentic development, ensuring alignment with security, privacy, and regulatory expectations.
• Develop solutions that account for non‑functional requirements such as scalability, performance, resiliency, security, privacy, and regulatory compliance, including AI‑specific requirements such as model monitoring, explainability, and secure inference.
• Communicate with clients and stakeholders to analyze business requirements, data needs, and processes; produce architecture recommendations that align business, technology, data, and AI strategies, prioritizing high‑value AI use cases.
• Oversee architecture outcomes across initiatives, ensuring solution, data, and AI architectures meet functional, non‑functional, and governance requirements at each phase.
• Collaborate with enterprise data governance and risk partners to ensure architectures align with data governance, security, privacy, regulatory standards, and model risk management, including GenAI controls.
• Explore new and emerging technologies and capabilities such as cloud‑native data services, GenAI, AI/ML platforms, vector search, streaming, agent frameworks, metadata and governance tooling, developing strategic viewpoints on how they enable business outcomes.
• Practice strong decision making and critical thinking by fully analyzing complex business, technology, and data issues and driving productive, well‑reasoned outcomes.
• Practice enterprise systems thinking, with a broad understanding of application, infrastructure, integration, and data architectures and how they collectively enable business capabilities.

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for this role, including:

• Competitive Advantages, Customer Solutions, Design
• Enterprise Architecture Framework (TOGAF)
• Machine Learning (ML), Risk Assessments, Technical Knowledge
• Analytical Thinking, Effective Communications,…