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AI System Design Architect – Vice President
State Street. Own and drive enterprise-wide AI system architecture strategy across the full GenAI platform stack .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI system architecture, including Generative AI, cloud architecture on AWS, Azure, or Google Cloud, and compliance with Responsible AI standards. Proven ability to lead enterprise-wide architecture strategies and collaborate with cross-functional teams to drive scalable and secure AI solutions.
Highest-signal resume keywords
Generative AI ArchitectureCloud Architecture on AWS, Azure, or GCPAI Governance and ComplianceEnterprise Solution DesignLeadership in Architecture Discussions
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Solution ArchitectureEnterprise Application ArchitectureAI/ML ArchitectureAPI ArchitectureMicroservicesDistributed SystemsEvent-Driven PatternsDevSecOpsCI/CDPerformance Optimization
Soft Skills
LeadershipStakeholder ManagementProblem-SolvingCross-Functional CollaborationEffective Communication
Tools & Technologies
Cloud-Native ArchitectureAI/ML ServicesVector DatabasesPrompt Design/OrchestrationObservability ToolsMonitoring Tools
Industry Keywords
Responsible AIModel RiskComplianceTesting StandardsProduction Controls
Tech Stack
Tools & technologiesAWSAzureCloudDistributed SystemsGoogle Cloud PlatformMicroservices
About the role
Key responsibilities & impact- Own and drive enterprise-wide AI system architecture strategy across the full GenAI platform stack
- Define and govern reference architectures, design standards, architecture principles, integration patterns, and cloud design approaches
- Provide strategic technical leadership on scalable, secure, resilient, and compliant AI system design
- Lead architecture decisions for cloud and hybrid AI environments on AWS, Azure, or Google Cloud
- Establish reusable enterprise patterns for RAG, model serving, prompt orchestration, agentic AI workflows, AI gateways, and service integration
- Chair or lead architecture governance forums and review major solution designs
- Resolve technical trade-offs and ensure alignment with enterprise standards
- Partner with business leaders, product, engineering, cloud, security, risk, data, and operations teams
- Ensure AI solutions comply with Responsible AI, governance, data controls, model risk, testing standards, security requirements, and regulatory expectations
- Drive architecture assessments, technical due diligence, platform modernization, proof-of-concept direction, and production onboarding standards
- Guide enterprise decisions on platform capabilities, shared services, build-vs-buy evaluations, and modernization opportunities
- Influence and mentor architects and engineering leaders
- Represent the Architecture function in senior governance and leadership forums
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline
- 12–17 years of experience in solution architecture, enterprise application architecture, platform architecture, or AI/ML architecture, including leadership of large-scale enterprise initiatives
- Deep hands-on and architectural experience with Generative AI, LLMs, ML systems, RAG, vector databases, prompt design/orchestration, and AI application integration
- Proven expertise in cloud architecture and enterprise solution design on AWS, Azure, or Google Cloud Platform (GCP)
- Strong understanding of cloud-native architecture, including AI/ML services, networking, storage, security, IAM, resilience, and performance optimization
- Proven experience designing enterprise-scale, secure, resilient, and high-performing architectures for AI and data-driven applications
- Expertise in API architecture, microservices, distributed systems, event-driven patterns, enterprise integration, and platform design
- Strong understanding of AI governance, Responsible AI, model risk, compliance, testing, production controls, and control frameworks
- Strong understanding of DevSecOps, CI/CD, observability, monitoring, reliability engineering, and platform engineering concepts
- Demonstrated ability to lead architecture discussions with senior executives and communicate effectively with technical and non-technical stakeholders
- Strong leadership, stakeholder management, problem-solving, and cross-functional collaboration skills
Benefits
Comp & perks- Retirement savings plan (401K) with company match
- Basic life insurance
- Medical insurance
- Dental insurance
- Vision insurance
- Long-term disability insurance
- Optional additional insurance coverages
- Paid vacation
- Paid sick leave
- Short-term disability
- Family care responsibilities leave
- Employee Assistance Program
- Incentive compensation, including eligibility for annual performance-based awards
- Certain tax-advantaged savings plans
- Inclusive development opportunities
- Flexible work-life support
- Paid volunteer days
- Employee networks