Software Engineering Group Manager - Data, Automation, & AI Architecture

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 Software Engineering Group Manager within PNC's Technology organization, you will be based in Philadelphia, PA; Columbus, OH; Dallas, TX; Phoenix, AZ; Pittsburgh, PA; Cleveland, OH; or Denver, CO

As a Software Engineering Group Manager within AMG Technology, you will lead an architecture team aligned exclusively to the Asset Management Group (AMG) line of business. The team will focus primarily on data, automation, and artificial intelligence architecture, translating AMG business priorities into practical technology strategies, target-state architectures, reference patterns, and delivery roadmaps. The role will partner closely with AMG business and technology leaders, Enterprise Architecture, Risk, Cybersecurity, Data Management, and delivery teams to modernize AMG capabilities and improve client and employee outcomes.

• Description
• This management-level position is responsible for building, leading, and maturing an AMG Technology architecture team dedicated to data, automation, and AI. The team will connect AMG's current-state environment to its future-state objectives by defining architecture direction, guiding solution design, evaluating technology options, and establishing reusable patterns appropriate for AMG's wealth and asset management businesses.
• The central mandate is to bolster the LOB-aligned architecture practice for AMG by helping evaluate, select, standardize, and responsibly scale data, automation, and AI capabilities. The team will identify opportunities to simplify the AMG technology landscape, improve data quality and accessibility, automate business processes, enable advanced analytics and AI use cases, and reduce unnecessary solution duplication within AMG.
• Candidates should have a strong background in data, solution, platform, automation, or AI/ML architecture, complemented by working knowledge of business architecture. Strong candidates will also understand financial services, wealth management, asset management, fiduciary responsibilities, privacy, model risk, cybersecurity, records management, and other control considerations relevant to the responsible use of data and AI.
• This position is highly visible and influential. It requires a strategic and deliberate leader who can build trusted relationships across AMG, develop architecture talent, communicate clearly with executives and practitioners, and convert emerging business needs into actionable architecture decisions and roadmaps.

Key Responsibilities

Team Leadership & Development

• •Build, lead, mentor, and grow an AMG-aligned team of architects focused on data, automation, and AI domains.
• •Leverage and enhance the existing operating model, engagement framework, intake process, and architecture governance mechanisms for AMG Technology.
• •Align Data/Automation/AI architecture capacity and priorities to AMG strategy, annual planning, investment decisions, regulatory commitments, and delivery needs.
• •Foster continuous learning, intellectual curiosity, disciplined engineering, and collaboration across AMG architecture and delivery teams.
• •Manage talent acquisition, performance, career development, and succession planning for direct reports.
• •Promote an inclusive, respectful, and psychologically safe team environment aligned with PNC values.

AMG Architecture, Strategy & Decision Authority

• •Serve as the primary design and decision authority within AMG Technology for data, automation, and AI architecture, operating within enterprise standards and governance.
• •Develop and maintain AMG technology strategies, target-state architectures, reference architectures, standards, patterns, and roadmaps for data, automation, and AI.
• •Lead evaluations of products, tools, platforms, and capabilities, translating findings into clear recommendations, architecture decisions, adoption guidance, and investment options for AMG.
• •Guide data, automation and AI solution teams in applying architecture principles across the lifecycle of strategy, discovery, design, planning, delivery, and modernization.
• •Identify reusable components and common patterns across AMG portfolios to increase consistency, reduce duplication, and accelerate time to value.
• •Ensure architecture decisions address quality attributes including security, privacy, scalability, resilience, observability, performance, interoperability, supportability, and regulatory compliance.
• •Partner with Enterprise Architecture and control functions to ensure AMG solutions comply with enterprise policies while meeting AMG-specific business needs.

Data Architecture & Enablement

• •Define AMG data architecture direction across operational, analytical, and AI use cases, including data integration, data products, metadata, lineage, quality, governance, semantic consistency, and consumption patterns.
• •Partner with AMG data owners, stewards, engineering teams, analytics teams, and business leaders to make trusted data easier to discover, understand, access, and use responsibly.
• •Guide modernization of AMG data platforms and integration patterns, balancing strategic target-state direction with pragmatic transition architectures.
• •Promote governed reuse of data and analytics capabilities across AMG while protecting confidential, client, employee, and regulated information.
• •Establish architecture patterns that support reporting, advanced analytics, machine learning, generative AI, and agentic solutions using fit-for-purpose, well-controlled data.

Automation Architecture

• •Define the AMG automation architecture strategy across workflow, orchestration, intelligent document processing, robotic process automation, APIs, events, low-code capabilities, and AI-assisted automation.
• •Partner with AMG product and operations teams to identify high-value automation opportunities and select architecture approaches based on business value, risk, complexity, maintainability, and control requirements.
• •Promote reusable automation patterns, integration services, and controls that reduce manual effort and improve reliability within AMG processes.
• •Guide teams away from brittle point solutions by establishing sustainable automation patterns with clear ownership, monitoring, exception handling, and lifecycle management.

AI Architecture & Responsible Adoption

• •Define AMG AI architecture strategy and reference patterns for machine learning, generative AI, copilots, retrieval-augmented generation, and agentic AI use cases.
• •Guide the responsible introduction and scaling of AI capabilities within AMG, including appropriate human oversight, data protection, model and solution governance, traceability, testing, monitoring, and risk management.
• •Partner with AMG business, product, data science, engineering, risk, legal, compliance, cybersecurity, and enterprise AI stakeholders to evaluate use cases and architecture options.
• •Lead proofs of concept and structured experimentation when needed to validate value, feasibility, integration approach, control requirements, and production readiness.
• •Monitor AI and automation trends and translate them into practical implications, opportunities, guardrails, and roadmaps for AMG.

Consulting, Communication & Stakeholder Engagement

• •Provide strategic consultation to AMG business and technology leaders on data, automation, and AI capabilities, architecture choices, capability gaps, and long-term roadmaps.
• •Analyze AMG business capabilities, processes, information needs, and technology constraints to develop recommendations grounded in business outcomes, enterprise standards, and sound engineering principles.
• •Develop and present architectu