{"id":3489368,"url":"https://alion.io/job/pnc-financial-services-group-software-engineering-group-manager-data-automation-ai-architecture","title":"Software Engineering Group Manager - Data, Automation, & AI Architecture","company":{"id":4228,"name":"PNC Financial Services Group","domain":"pnc.com","url":"https://alion.io/company/pnc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":278,"ghost_share":0,"stale_share":0.734,"repost_share":0.007,"time_to_fill_p50_days":30,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Leadership","role_family":"Leadership","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Denver, United States","Columbus, United States","Dallas, United States","Phoenix, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":109000,"max_usd":209000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":151},"experience_years_min":8,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Machine Learning","optional":false},{"name":"RAG","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true}],"status":"live","first_seen_at":"2026-10-27T00:00:00Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-11-03T01:54:33Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Position Overview\nAt 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, COAs 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.\nDescription\nThis 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.\nThe 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.\nCandidates 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.\nThis 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.\nKey Responsibilities\nTeam Leadership & Development\nBuild, lead, mentor, and grow an AMG-aligned team of architects focused on data, automation, and AI domains.\nLeverage and enhance the existing operating model, engagement framework, intake process, and architecture governance mechanisms for AMG Technology.\nAlign Data/Automation/AI architecture capacity and priorities to AMG strategy, annual planning, investment decisions, regulatory commitments, and delivery needs.\nFoster continuous learning, intellectual curiosity, disciplined engineering, and collaboration across AMG architecture and delivery teams.\nManage talent acquisition, performance, career development, and succession planning for direct reports.\nPromote an inclusive, respectful, and psychologically safe team environment aligned with PNC values.\nAMG Architecture, Strategy & Decision Authority\nServe as the primary design and decision authority within AMG Technology for data, automation, and AI architecture, operating within enterprise standards and governance.\nDevelop and maintain AMG technology strategies, target-state architectures, reference architectures, standards, patterns, and roadmaps for data, automation, and AI.\nLead evaluations of products, tools, platforms, and capabilities, translating findings into clear recommendations, architecture decisions, adoption guidance, and investment options for AMG.\nGuide data, automation and AI solution teams in applying architecture principles across the lifecycle of strategy, discovery, design, planning, delivery, and modernization.\nIdentify reusable components and common patterns across AMG portfolios to increase consistency, reduce duplication, and accelerate time to value.\nEnsure architecture decisions address quality attributes including security, privacy, scalability, resilience, observability, performance, interoperability, supportability, and regulatory compliance.\nPartner with Enterprise Architecture and control functions to ensure AMG solutions comply with enterprise policies while meeting AMG-specific business needs.\nData Architecture & Enablement\nDefine 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.\nPartner with AMG data owners, stewards, engineering teams, analytics teams, and business leaders to make trusted data easier to discover, understand, access, and use responsibly.\nGuide modernization of AMG data platforms and integration patterns, balancing strategic target-state direction with pragmatic transition architectures.\nPromote governed reuse of data and analytics capabilities across AMG while protecting confidential, client, employee, and regulated information.\nEstablish architecture patterns that support reporting, advanced analytics, machine learning, generative AI, and agentic solutions using fit-for-purpose, well-controlled data.\nAutomation Architecture\nDefine the AMG automation architecture strategy across workflow, orchestration, intelligent document processing, robotic process automation, APIs, events, low-code capabilities, and AI-assisted automation.\nPartner 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.\nPromote reusable automation patterns, integration services, and controls that reduce manual effort and improve reliability within AMG processes.\nGuide teams away from brittle point solutions by establishing sustainable automation patterns with clear ownership, monitoring, exception handling, and lifecycle management.\nAI Architecture & Responsible Adoption\nDefine AMG AI architecture strategy and reference patterns for machine learning, generative AI, copilots, retrieval-augmented generation, and agentic AI use cases.\nGuide 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.\nPartner with AMG business, product, data science, engineering, risk, legal, compliance, cybersecurity, and enterprise AI stakeholders to evaluate use cases and architecture options.\nLead proofs of concept and structured experimentation when needed to validate value, feasibility, integration approach, control requirements, and production readiness.\nMonitor AI and automation trends and translate them into practical implications, opportunities, guardrails, and roadmaps for AMG.\nConsulting, Communication & Stakeholder Engagement\nProvide strategic consultation to AMG business and technology leaders on data, automation, and AI capabilities, architecture choices, capability gaps, and long-term roadmaps.\nAnalyze AMG business capabilities, processes, information needs, and technology constraints to develop recommendations grounded in business outcomes, enterprise standards, and sound engineering principles.\nDevelop and present architecture deliverables including capability models, context diagrams, information flows, current- and future-state architectures, reference architectures, architecture decisions, transition plans, and roadmaps.\nFacilitate architecture reviews and decision forums, making trade-offs, assumptions, risks, dependencies, and recommended decisions explicit.\nCommunicate complex technology topics clearly to senior executives, business partners, engineers, architects, governance bodies, and control partners.\nSuccessful Candidates Will Possess\nProven experience leading and developing architecture or senior engineering teams, with a record of building high-performing, collaborative groups.\nStrong depth in data architecture and engineering, intelligent automation, AI/ML architecture, or solution/platform architecture, with practical breadth across the other domains.\nExperience creating data strategies, target-state architectures, integration patterns, data governance approaches, and analytics or AI enablement roadmaps.\nExperience evaluating enterprise products, tools, and platforms and translating evaluations into decisions, reference architectures, implementation guidance, and measurable outcomes.\nAbility to connect AMG business capabilities and operating processes to technology strategies and architecture decisions.\nKnowledge across architecture disciplines including Business, Application, Solution, Data, Technology, Integration, and Security Architecture.\nWorking knowledge of technologies such as data integration and analytics platforms, data catalogs and governance tools, AI/ML platforms, generative AI, workflow and automation platforms, APIs, middleware, event streaming, cloud services, and modern application architectures.\nAbility to create high-quality architecture deliverables including capability models, reference architectures, context diagrams, information flows, strategy maps, current/future-state architectures, architecture decision records, and roadmaps.\nDemonstrated ability to influence without direct authority, resolve ambiguity, and drive decisions among business, technology, architecture, delivery, risk, and control stakeholders.\nStrong financial services knowledge; experience in wealth management, asset management, investments, trust, brokerage, or related AMG domains is highly valued.\nUnderstanding of responsible AI, data privacy, cybersecurity, records management, model risk, third-party risk, and regulatory considerations relevant to data, automation, and AI solutions.\nProfessional certifications are a plus, such as TOGAF, SAFe, AWS/Azure/GCP Data or AI certifications, data management credentials, or automation platform certifications.\nKey Characteristics\nPeople-first leader who attracts, retains, and develops strong architecture talent.\nAMG-focused partner who understands business priorities and converts them into clear architecture direction.\nOrganizationally savvy facilitator who works effectively across business, technology, risk, and enterprise governance teams.\nRespected and trusted leader who is outcome-oriented, evidence-based, and vendor-neutral.\nIntellectually curious, pragmatic, and disciplined in balancing innovation, delivery speed, risk, and long-term sustainability.\nComfortable operating in ambiguity and creating clarity in complex, highly regulated environments.\nMotivated by measurable AMG business outcomes, improved client and employee experiences, and durable technology capabilities.\nPNC Values\nPNC employees take pride in our reputation and are expected to be:\nCustomer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in business decisions, and able to use that understanding to create customized customer solutions.\nManaging Risk - Assessing and effectively managing the risks associated with business objectives and activities to ensure alignment with PNC's Enterprise Risk Management FrameworkPNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. 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