Mainframe Modernization Architect -- EX90975938430

Key Responsibilities

• Lead architecture strategy and solution design for complex enterprise technology initiatives.
• Assess legacy and mainframe applications and develop modernization plans, including decomposing monolithic systems and moving toward cloud-ready platforms.
• Design cloud-native, distributed solutions using APIs, microservices, events, and enterprise integration patterns.
• Apply Domain Driven Design principles to organize systems around business domains and bounded contexts.
• Partner with Enterprise Architects, Product Management, business stakeholders, engineers, vendors, and Agile Release Train teams to develop technology roadmaps.
• Create solution blueprints, target-state architectures, integration designs, architecture decision records, and technical standards.
• Define requirements for scalability, resiliency, performance, security, and maintainability, and guide teams through architecture trade-offs.
• Evaluate AI, automation, intelligent workflows, and predictive analytics opportunities through workshops, proofs of concept, prototyping, and feasibility analysis.
• Establish architecture governance and responsible AI practices addressing security, privacy, compliance, regulatory requirements, and enterprise risk.
• Develop technical debt reduction plans and promote engineering practices across DevSecOps, CI/CD, and the software development lifecycle.
• Coach architects, engineers, and analysts on solution design, systems thinking, and modern architecture practices.
• Communicate recommendations, risks, investment considerations, and business value to technical and business stakeholders.

Required Qualifications

• 8 years of progressively increasing responsibility and leadership in architecture, enterprise architecture, software engineering, solution design, or modernization within complex, large-scale organizations.
• Required experience assessing and modernizing mainframe and legacy systems into scalable, secure, maintainable, cloud-ready platforms.
• Expert-level knowledge of cloud-native, distributed, and event-driven architectures, including APIs, microservices, and integration patterns.
• Advanced technical knowledge of AWS, Java, containerization, mainframe technologies, legacy and modern programming languages, and relational and non-relational databases.
• Experience designing enterprise systems that use APIs and events as primary integration mechanisms.
• Experience applying Domain Driven Design, including business domains and bounded contexts.
• Ability to guide teams through distributed system design decisions involving performance, scalability, resiliency, integration, and technical trade-offs.
• Experience with DevSecOps, CI/CD, and software development lifecycle management.
• AI and data architecture experience, including evaluating and implementing AI, automation, intelligent workflows, and predictive analytics solutions.
• Experience establishing governance, security, privacy, compliance, responsible AI, and enterprise risk management practices.
• Leadership experience in Agile and SAFe environments, working across business, product, architecture, and engineering teams.
• Strong communication, stakeholder management, strategic thinking, risk evaluation, and organizational change leadership skills.

Preferred Qualifications

• TOGAF certification.
• Insurance industry experience.
• Experience with AWS services and tools such as S3, Bedrock, SageMaker, EC2, Amazon Connect, CDK, and SDKs.
• Practical familiarity with autonomous AI systems.
• Participation in industry groups or architecture and engineering communities of practice.

Top Skillsets

1. Mainframe and Legacy Modernization – Assessing legacy applications, decomposing monoliths, and transitioning systems to cloud-ready platforms.
2. AWS and Cloud-Native Architecture – Designing cloud solutions using AWS, containers, and microservices.
3. Distributed and Event-Driven Systems – Designing scalable, resilient systems and understanding performance and architecture trade-offs.
4. API Design and Enterprise Integration – Using APIs, events, and integration patterns to connect enterprise applications.
5. Java and Enterprise Technologies – Technical depth in Java, mainframe technologies, and relational and NoSQL databases.
6. Domain Driven Design (DDD) – Structuring applications around business domains and bounded contexts.
7. AI and Data Architecture – Evaluating and implementing AI, automation, intelligent workflows, and predictive analytics with appropriate governance.