Enterprise Architect

Role Summary:

The Enterprise Architect shapes and governs the enterprise technology landscape of Upbound that involves Fintech, Specialty Financing, and Retail business to enable strategy, accelerate product delivery, and reduce complexity and risk. This role defines enterprise-wide architecture across business, application, data, integration, technology, and security, establishes standards and reference architectures, and partners with product, engineering, risk, compliance, data, and platform teams to ensure solutions are scalable, resilient, cost-effective, and compliant.

The role operates in federated architecture model: cloud, network, security, commerce, mobile, and other platform architects are embedded in their respective organizations and do not report into the EA organization. The Enterprise Architect drives cross-domain coherence, aligns platform to enterprise needs, and ensures end-to-end solutions integrate cleanly and meet non-functional requirements.

What you will do (core responsibilities)

• Enterprise architecture strategy

  • Define and maintain enterprise architecture vision, principles, target-state architectures, and multi-year roadmaps aligned to business strategy – growth, conversion, loss reduction, and servicing efficiency.

  • Drive modernization, rationalization, and simplification across applications, platforms, and data domains spanning customer identity, underwriting/risk, fraud, pricing/discounting, payments/collections, servicing, customer engagement and customer communications​

• Federated architecture leadership (matrix influence)

  • Lead enterprise architecture outcomes in a federated model by partnering with embedded architects across cloud, network, security, commerce, mobile, and platform engineering

  • Align enterprise standards and target-state direction with platform reference architectures and ensure consistent adoption across product pods

  • Influence cross-team decisions through architecture forums, ADRs, and exception governance – driving outcomes without direct reporting authority

• Architecture governance and decisioning

  • Lead architecture reviews (L2/L3, design authority, ARB) focused on cross-domain decisions – domain boundaries, integration approach, data contracts, security objectives, NFRs, exceptions.

  • Establish lightweight, outcome-based guardrails that support agile delivery – reference architectures, patterns, and decision records.

  • Maintain ADRs, exception management, and time bound remediation plans.

• Cross-domain architecture leadership

  • Partner with Solution Architects and Engineering Leads to design end-to-end solutions align with enterprise target state, domain boundaries, reference architectures, and cross-domain standards for data, integration, security, NFRs

  • Ensure architectural consistency across product pods and shared platforms (customer identity & profile, commerce, underwriting services, servicing platforms, communication & engagement platforms, integrating/eventing, data/analytics, security)

• Standards, reference architectures, and reuse

  • Develop and publish enterprise reference architectures and standards for:

    • Integration (API/event/streaming), data/analytics, identity/IAM, security by design, observability, resiliency, and DevSecOps

    • Interoperability guardrails across platforms

  • Create reusable patterns and components to reduce time-to- market and improve reliability especially around data contracts, event schemas, identity resolution, decisioning workflows, and auditability

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• Portfolio and technology planning

  • Influence investment decisions by translating architecture options into tradeoffs – cost, time, risk scalability, maintainability, operability, vendor lock-in

  • Support vendor evaluations and build-vs-buy recommendations with clear criteria and decision records – especially where solutions cross domains or create enterprise-wide dependencies

• Risk, security, and compliance

  • Embed security and compliance into enterprise design – zero trust objectives, IAM, encryption/tokenization where needed, privacy-by-design, audit logging, data retention.

  • Partner with Security/GRC and Risk to ensure architectures meet regulatory obligations and internal controls common to financial services

  • Focus on security objectives and design patterns; collaborate with embedded security architects for control implementation details

• Data and integration architecture

  • Define enterprise data architecture guardrails (canonical models, master/reference data, lineage, governance, access controls) and integration strategy (APIs/events/streaming)

  • Ensure clean interoperability between operational systems and analytics/AI platforms through consistent contracts, metadata, and access patterns

• Enterprise AI/GenAI architecture

  • Define enterprise AI patterns and guardrails: secure RAG, least-privilege data access, governance, evaluation and monitoring, prompt/response logging where appropriate, and cost/latency guardrails for inference

  • Establish production-ready approaches for AI in regulated contexts

  • Partner with data/AI teams and platform teams to move AI from POCs to production with strong operational rigor

• Architecture artifacts and communication

  • Maintain capability maps, architecture diagrams, target-state roadmaps, ADRs, and standards in an accessible repository

  • Communicate complex concepts clearly to executives and delivery teams – what changes, why it matters, and tradeoffs.

What success looks like

• Reduced architecture drift, measurable adherence to standards with fewer exceptions

• Faster delivery through reusable patterns and clearer guardrails across product pods

• Fewer critical production incidents tried to cross-domain design issues, improved resiliency, and operability posture

• Lower run costs through rationalization and simplification – application, integrations, tech debt.

• Improved security/compliance posture with stronger auditability and fewer control gaps

• AI initiatives that progress from POC  production with clear governance, monitoring, and cost controls

• Improved alignment between product/domain roadmaps and platforms without duplicating platform architecture ownership.

Who you will work with

• Product Management/Product Owners, Engineering Managers, Tech Leads

• Solution Architects, Business Architects and strategy teams

• Embedded platform architects – Commerce, Mobile, Platform Engineering, Cloud, Network, Security

• Security/GRC, Risk, Legal/Compliance, Infrastructure/Cloud, Data & Analytics / AI teams

• Program/Delivery leadership

Required qualifications

• 8 – 15+ years in architecture roles (enterprise, domain, or principal engineering) with demonstrated cross-domain impact

• Strong understanding of business capability modeling, application/integration architecture, data architecture, enterprise technology guardrails, and security-by-design

• Experience operating in federated/matrix environment, influencing architects and engineering leaders without direct reporting authority

• Proven experience establishing target-state architectures, roadmaps, and governance that supports agile teams.

• Ability to lead tradeoff discussions with executives and delivery teams – cost/risk/time/value

• Excellent communication skills; ability to produce executive-ready artifacts

• Experience in Fintech, lending, specialty financing, payments, or regulated financial services

Preferred qualifications

• Experience building or scaling an EA practice – operating model, standards, governance, reference architectures

• Experience in large-scale modernization – legacy rationalization, cloud migration, platform transformation

• Familiarity with architecture frameworks

• Experience with event-driven architecture, API management, and data platforms/warehouse/lakehouse patterns

• Experience with security architecture concepts – zero trust, IAM, data protection, and compliance environments

• Experience with AI/GenAI architecture patterns (RAG, evaluation, monitoring, LLMOps) in enterprise environments

Core competencies

• Systems thinking and pragmatism – guardrails over gatekeeping

• Influencing without authority

• Strong facilitation and stakeholder management

• Decision discipline (ADRs, principles, measurable outcomes)

• Bias toward simplification and reuse