Software Engineering Group Manager- Artificial Intelligence at PNC Financial Services in Pittsburgh, PA

  • Company: PNC Financial Services
  • Location: PA - Pittsburgh (15219)
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-14

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Job description

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 Manager within PNC's Technology organization, you will be based in Pittsburgh, PA. PNC is seeking a Software Engineering Group Manager to lead a large-scale AI Engineering organization responsible for designing, building, and scaling enterprise Artificial Intelligence solutions that drive innovation across the bank. This leader will oversee an engineering team focused on advancing AI platforms, frameworks, and development patterns that enable future AI-powered business capabilities. The ideal candidate brings a unique blend of technical depth, AI engineering expertise, and proven people leadership. This individual will lead a team of highly skilled engineers who drive architecture and innovation efforts across the organization. The role requires a leader who can establish engineering strategy, influence technology direction, and enable teams to deliver scalable, secure, and production-ready AI solutions. Key Responsibilities: • Leadership & Organizational Management ○ Build a high-performing engineering culture focused on velocity, innovation, accountability, collaboration, and continuous learning. ○ Inspire and retain top AI and software engineering talent while creating clear career progression opportunities. ○ Establish organizational goals, workforce planning strategies, and talent development programs aligned to business priorities. ○ Partner with senior technology leaders to define long-term engineering strategy and investment priorities. ○ Create an environment where senior technical leaders can effectively drive innovation while maintaining delivery excellence. ○ Manage capacity planning, hiring, budgeting, and resource allocation across multiple initiatives and workstreams. • AI Engineering Strategy & Technical Leadership ○ Define and execute the AI engineering roadmap, identifying technologies, frameworks, and tooling that enhance current and future AI capabilities. ○ Evaluate emerging AI technologies and engineering patterns to drive innovation and improve developer productivity. ○ Provide technical oversight for the design, development, and deployment of enterprise-scale AI solutions. ○ Guide architectural decisions across AI applications, machine learning platforms, generative AI solutions, and intelligent automation initiatives. ○ Partner with senior engineers and architects to establish engineering standards, reusable frameworks, and scalable development practices. ○ Ensure AI solutions are built with security, resiliency, observability, and governance requirements embedded from inception. ○ Maintain sufficient hands-on knowledge of AI engineering trends, platforms, and tools to effectively lead technical discussions and decision-making. • Software Engineering Delivery ○ Lead the successful delivery of AI-powered products and platform capabilities from concept through production. ○ Establish and enforce software development lifecycle (SDLC) best practices, including code quality, automated testing, CI/CD, and release management. ○ Drive adoption of modern engineering practices, cloud-native architectures, and platform engineering capabilities. ○ Partner with product, architecture, data, and infrastructure teams to deliver scalable, enterprise-grade solutions. ○ Ensure engineering teams meet commitments for quality, performance, availability, and security. • Stakeholder Partnership & Influence ○ Collaborate with executive and business stakeholders to identify opportunities where AI can drive measurable business outcomes. ○ Translate strategic business objectives into technology initiatives and engineering priorities. ○ Com

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