Solution Architect Senior - AI/ML Architecture

Solution Architect Senior

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. It interacts with senior business and technology leaders, SMEs, and business architecture partners to bridge current state needs with future state objectives, culminating in technology, data, and AI strategies and solution architectures that enable business outcomes and drive transformation. In this role, you will draw upon deep business, technology, data, and AI/ML architecture experience to partner with key stakeholders and ensure that strategic perspectives, architectures, artifacts, and roadmaps are well crafted, clearly communicated, and achieve stakeholder consensus. You will be required to understand complex business processes, system interactions, and data flows to develop modern, scalable architectures that support large scale transformation initiatives, including AI-enabled products, analytics, and automation use cases. Candidates should have a strong background in solution, platform, system, application, and data architecture, with solid working knowledge of business architecture, and demonstrated experience enabling AI/ML and Generative AI (GenAI) capabilities at enterprise scale. This role will assess and drive integration, data, and AI platform strategies to gain operational efficiencies, optimize product offerings, and deliver a compelling client value proposition—ensuring the bank's portfolio of business capabilities, data assets, models, and enabling platforms are leveraged to their full potential. This position is highly visible and influential, demanding the ability to be strategic, conscientious, and deliberate. The role requires proven thought leadership, strong networking and interpersonal skills, political and emotional intelligence, excellent written communication, and the ability to understand and anticipate emerging business needs, data requirements, AI capabilities, and technology trends—while partnering with risk and governance teams to promote responsible AI (e.g., model risk management, fairness, explainability, privacy, and security).

This role:

• Develops solution, data, and AI/ML architecture and resolves complex issues across a variety of initiatives through requirements analysis, architectural leadership, and project supervision.
• Designs 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.
• Defines and governs 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 (quality, timeliness, lineage, and feature availability).
• Provides architectural leadership for data platforms and data ecosystems, including data warehousing, data lakes/lakehouses, analytical platforms, streaming architectures, and cloud based data services—enabling AI/ML platforms (e.g., feature stores, model training and inference services) where appropriate.
• Establishes and enforces best practices for data modeling (conceptual, logical, physical), data integration, data quality, metadata management, lineage, and lifecycle management, including practices that support model governance and auditability.
• Partners 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.
• Provides 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 enablement of agentic coding workflows (e.g., AI-assisted development, test generation, code review, and secure SDLC integration).
• Defines reference architectures, patterns, and guardrails for agentic development (e.g., repository-aware coding agents, workflow orchestration, prompt/tool governance, evaluation, and telemetry), ensuring alignment with security, privacy, and regulatory expectations.
• Develops solutions that account for non functional requirements (e.g., scalability, performance, resiliency, security, privacy, and regulatory compliance) and applies appropriate architectural tactics to meet them, including AI-specific requirements such as model monitoring, explainability, and secure inference.
• Communicates with clients and stakeholders to analyze business requirements, data needs, and processes; produces architecture recommendations that align business, technology, data, and AI strategies, including prioritizing high-value AI use cases and required capabilities.
• Oversees architecture outcomes across initiatives, ensuring solution, data, and AI architectures meet functional, non functional, and governance requirements at each phase.
• Collaborates with enterprise data governance and risk partners to ensure architectures align with data governance, security, privacy, regulatory standards, and model risk management (including appropriate controls for GenAI where applicable).
• Explores new and emerging technologies and capabilities (e.g., cloud-native data services, GenAI and AI/ML platforms such as Microsoft AI Foundry, vector search, streaming, agent frameworks/orchestration, metadata and governance tooling), developing strategic viewpoints on how they enable business outcomes or introduce disruption.
• Practices strong decision making and critical thinking by fully analyzing complex business, technology, and data related issues and driving productive, well reasoned outcomes.
• Practices enterprise systems thinking, with a broad understanding of application, infrastructure, integration, and data architectures and how they collectively enable business capabilities.

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals. PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.