Enterprise Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Enterprise Architect based in the United States.

The Enterprise Architect will shape the organization's technology strategy by aligning business objectives with secure, scalable, and cost-effective enterprise architecture. This senior leadership role spans business, data, applications, and technology platforms, ensuring that strategic priorities translate into practical implementation roadmaps. You will work closely with business leaders, architects, engineers, and executive stakeholders to modernize systems, improve operational efficiency, and strengthen enterprise capabilities. A key focus will be leveraging AI to accelerate architectural analysis, improve decision-making, and optimize delivery while maintaining responsible governance and compliance. You will establish architecture standards, guide complex technology investments, and reduce technical debt across a diverse enterprise environment. This remote opportunity offers the chance to influence large-scale transformation and support innovation across advanced manufacturing and other critical industries.

Accountabilities:

As the Enterprise Architect, you will define and govern the organization's enterprise architecture across business processes, data, applications, and technology platforms. You will ensure architectural decisions support strategic goals, operational resilience, security, and measurable business value. Key responsibilities include:

• Business architecture and strategic alignment: Develop and maintain capability maps, value streams, process models, and organizational impact assessments. Connect architecture roadmaps to business outcomes, benefits, and performance metrics, maintaining traceability from strategy through implementation.

• Enterprise data architecture: Establish data principles, domain models, integration patterns, governance frameworks, and quality standards. Design data platforms that support analytics, AI and machine learning, streaming, event processing, and real-time decision-making. Define data ownership, stewardship, lineage, privacy, and security practices with relevant stakeholders.

• Responsible AI architecture: Ensure data and AI designs incorporate model governance, bias monitoring, explainability, and auditability. Establish architectural patterns and guardrails for enterprise AI, including data requirements, MLOps, model lifecycle management, and compliance.

• Application architecture and modernization: Define target-state application architecture that promotes modularity, interoperability, scalability, and long-term sustainability. Encourage API-first, cloud-native, AI-native, event-driven, and reusable component patterns while guiding microservices boundaries and domain design.

• Technology and platform architecture: Develop blueprints for platforms, infrastructure, integration layers, and cloud environments, including hybrid and multi-cloud configurations where appropriate. Ensure architectures support DevSecOps, Infrastructure as Code, observability, automation, resilience, and security by design.

• Architecture governance and standards: Establish and maintain enterprise architecture policies, standards, reference architectures, models, roadmaps, and technical guardrails. Lead architecture review boards and initiative checkpoints, assess compliance, manage exceptions, and guide build-versus-buy decisions, risk tradeoffs, and technical debt management.

• Security, resilience, and compliance: Embed zero-trust principles, security by design, privacy, auditability, and applicable industry requirements into architectural patterns. Conduct threat modeling and resilience planning, defining approaches to business continuity, disaster recovery, reliability, and supply-chain security.

• Roadmap development and portfolio rationalization: Use current-state and target-state models, impact assessments, and gap analyses to develop actionable roadmaps. Translate these into implementation plans, epics, milestones, acceptance criteria, and measurable business outcomes. Rationalize application portfolios, eliminate redundancies, reduce technical debt, and guide modernization and migration initiatives.

• AI-enabled architectural efficiency: Apply AI tools to model dependencies, identify risks, estimate impacts, optimize designs, and detect architectural patterns. Use generative AI to accelerate documentation, standards development, scenario modeling, solution design, and governance workflows.

• Execution optimization and delivery leadership: Guide delivery teams through design, build, and release, making timely architectural decisions and removing blockers. Monitor execution against architecture objectives, address deviations, and validate post-implementation outcomes for alignment, security, compliance, and time to value.

• Strategic advisory and team development: Advise senior…