Corporate Functions Senior Solutions Architect – VP

Who We Are Looking For

We are seeking a senior, hands-on technology leader to serve as the Corporate Functions Senior Solutions Architect – VP III , responsible for defining, scaling, and governing the next generation of AI-enabled platforms across Corporate Functions globally.

This role will lead the architecture and evolution of enterprise AI capabilities, transforming today's knowledge assistants and AI-powered employee experiences into a scalable ecosystem of intelligent agents capable of securely interacting with employees, enterprise systems, business processes, and external platforms.

The ideal candidate is a highly technical architect with deep expertise in AI platform architecture, agentic AI, cloud-native engineering, enterprise integrations, orchestration frameworks, and large-scale solution design . This individual will establish architectural standards, guide global engineering teams, influence enterprise technology strategy, and ensure AI capabilities are secure, resilient, scalable, and operationally mature.

This is a highly visible leadership role partnering across Human Resources, Legal, Audit, Compliance, Risk, Data, Enterprise Architecture, Cybersecurity, Infrastructure, and Business Leadership to accelerate AI adoption while maintaining strong governance, security, and regulatory controls.

Why This Role Matters

Corporate Functions is investing in AI-enabled capabilities that will fundamentally transform how employees access information, execute work, automate processes, and interact with enterprise systems.

This role is responsible for creating the architecture and operating model required to scale those capabilities globally. You will define how intelligent agents interact with people, applications, data, workflows, and business processes while ensuring solutions are secure, compliant, observable, and aligned with enterprise standards.

You will:

• •Define the future-state AI platform architecture for Corporate Functions.
• •Establish reusable patterns for agentic AI, orchestration, automation, and enterprise integrations.
• •Scale AI capabilities across multiple business domains and geographies.
• •Drive modernization toward cloud-native, event-driven, API-first architectures.
• •Enable secure interactions between AI agents, employees, and enterprise systems.
• •Create architecture standards that accelerate innovation while maintaining strong governance and operational controls.

This is an opportunity to shape the future of AI across Corporate Functions while delivering tangible business impact at enterprise scale.

What You Will Be Responsible For

1. AI Platform Strategy & Architecture Leadership

• •Define and own the architecture strategy, target-state roadmap, and technology standards for AI-enabled solutions across Corporate Functions.
• •Lead the evolution of enterprise AI capabilities from knowledge assistants and productivity tools into intelligent, workflow-driven AI ecosystems.
• •Develop reusable architecture patterns supporting:
• •Agentic AI
• •Multi-agent orchestration
• •Human-in-the-loop workflows
• •Autonomous workflow execution
• •AI-driven decision support
• •Enterprise tool integration
• •Workflow automation
• •Intelligent process orchestration

Establish enterprise standards for scalability, reliability, security, governance, and operational readiness.

2. Agentic AI & Multi-Agent Orchestration

• •Define architecture patterns for intelligent agents capable of planning, reasoning, coordinating, and executing business workflows.
• •Design and scale solutions leveraging:
• •Agent-to-Agent (A2A) communication
• •Agent orchestration frameworks
• •Tool calling and workflow execution
• •Agent memory and context management
• •Decisioning and escalation workflows
• •Task decomposition and planning
• •Human oversight and exception handling

• •Enable agents to securely collaborate across business domains and technology platforms.
• •Establish governance standards for agent behavior, auditability, transparency, and operational controls.
• •Design architectures that support future AI-native business operating models.

3. Enterprise AI Engineering & AWS Architecture

• •Define scalable cloud architecture patterns supporting AI workloads and enterprise platform services.
• •Partner with Engineering, Infrastructure, and Cloud teams to establish production-ready solutions utilizing AWS-native services.
• •Guide architecture across:
• •Compute services
• •AI model integration
• •Event-driven architectures
• •Messaging platforms
• •API services
• •Serverless architectures
• •Data services
• •Security and identity controls

• •Ensure solutions are engineered for:
• •High availability
• •Disaster recovery
• •Performance optimization
• •Cost efficiency
• •Autoscaling
• •Global deployment
• •Operational resiliency

4. Enterprise Integration & Agent-to-Agent Connectivity

• •Architect secure integrations between AI platforms and enterprise systems.
• •Define standards enabling intelligent agents to interact with:
• •Workday
• •ServiceNow
• •Microsoft 365
• •SharePoint
• •Databricks
• •Internal enterprise applications
• •External SaaS platforms
• •Vendor-hosted solutions

• •Design reusable API frameworks and event-driven integration patterns.
• •Enable intelligent workflow orchestration that spans multiple systems and business processes.
• •Drive adoption of enterprise integration standards supporting scalable automation and future AI initiatives.

5. Security, Governance & Responsible AI

• •Partner closely with Cybersecurity, Enterprise Architecture, Risk, Privacy, and Compliance organizations.
• •Ensure all AI solutions meet enterprise requirements for:
• •Authentication and authorization
• •Identity and access management
• •Data privacy and protection
• •Encryption
• •Regulatory compliance
• •Audit readiness
• •Operational governance
• •Responsible AI controls

• •Establish patterns for explainability, transparency, monitoring, and human oversight.
• •Support architecture reviews, risk assessments, cloud governance reviews, and production readiness processes.

6. Observability, Reliability & Operational Excellence

• •Define standards for monitoring, logging, tracing, performance management, and operational support.
• •Establish KPIs for:
• •Platform availability
• •Agent performance
• •Automation effectiveness
• •User adoption
• •Service quality
• •Operational health

• •Partner with engineering teams to implement production support models, runbooks, incident management processes, and resiliency testing.
• •Ensure enterprise AI solutions are maintainable, supportable, and scalable in a regulated environment.

7. Architecture Governance & Technical Leadership

• •Serve as a senior architecture authority across Corporate Functions Technology.
• •Lead architecture reviews and provide technical guidance on strategic initiatives.
• •Establish reusable reference architectures, standards, and engineering patterns.
• •Mentor architects, technical leads, and engineering teams.
• •Drive alignment across business, technology, infrastructure, cybersecurity, and vendor partners.
• •Promote a culture of engineering excellence, innovation, accountability, and continuous improvement.

8. Executive Partnership & Strategic Influence

• •Translate complex technical concepts into actionable business recommendations.
• •Influence technology strategy and investment decisions across Corporate Functions.
• •Partner with senior leaders to identify opportunities where AI can improve productivity, employee experience, automation, risk management, and operational efficiency.
• •Communicate architecture tradeoffs, risks, and recommendations clearly to executive stakeholders.
• •Build strong partnerships across global teams and organizational boundaries.

Must-Have Qualifications

• •15+ years of experience in enterprise technology, solution architecture, platform engineering, cloud architecture, or AI solution delivery.
• •Proven experience designing and scaling enterprise platforms within large, global organizations.
• •Deep expe