We are seeking an experienced AI Systems Design Architect (VP) to lead enterprise AI system architecture strategy across the full Generative AI platform stack. This role requires deep expertise in Generative AI, enterprise architecture, platform engineering, distributed systems, and scalable cloud architectures on AWS, Azure, or Google Cloud Platform (GCP).
The ideal candidate will define architecture direction, technology standards, and cloud design principles for AI platforms and shared services across the organization. This role will shape modernization priorities, represent Architecture in senior leadership and governance forums, and ensure AI systems are designed for security, resiliency, compliance, interoperability, and long-term scalability.
Key Responsibilities
Own and drive enterprise-wide AI system architecture strategy across the full GenAI platform stack, including shared services, orchestration layers, model integration, APIs, data flows, and downstream enterprise systems.
Define and govern reference architectures, design standards, architecture principles, integration patterns, and cloud design approaches for AI platforms and AI-enabled applications.
Provide strategic technical leadership on scalable, secure, resilient, and compliant AI system design across the organization.
Lead architecture decisions for cloud and hybrid AI environments on AWS, Azure, or Google Cloud, ensuring interoperability, platform reuse, cost efficiency, and operational excellence.
Establish reusable enterprise patterns for RAG, model serving, prompt orchestration, agentic AI workflows, AI gateways, and service integration.
Chair or lead architecture governance forums, reviewing major solution designs, resolving technical trade-offs, and ensuring alignment to enterprise standards.
Partner closely with business leaders, product teams, engineering, cloud, security, risk, data, and operations teams to align architecture strategy with business priorities.
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 for AI systems.
Guide enterprise decisions on platform capabilities, shared services, build-vs-buy evaluations, and modernization opportunities.
Influence and mentor architects and engineering leaders to improve design quality, architectural consistency, and adoption of enterprise AI standards.
Represent the Architecture function in senior governance and leadership forums.
Required Qualifications
Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline; Master’s degree preferred.
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 both technical and non-technical stakeholders.
Strong leadership, stakeholder management, problem-solving, and cross-functional collaboration skills.
Salary Range:
$120,000 - $217,500 AnnualThe range quoted above applies to the role in the location specified. If the candidate would ultimately work outside of the location above, the applicable range could differ.
Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.
For a full overview, visit https://hrportal.ehr.com/statestreet/Home.
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Skills Required
- Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or related discipline
- Master's degree
- 12-17 years experience in solution, enterprise application, platform, or AI/ML architecture including leadership of large-scale initiatives
- Hands-on and architectural experience with Generative AI, LLMs, ML systems, RAG, vector databases, prompt design and 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
- Experience designing enterprise-scale, secure, resilient, 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 with technical and non-technical stakeholders
- Leadership, stakeholder management, problem-solving, and cross-functional collaboration skills
State Street Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about State Street and has not been reviewed or approved by State Street.
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Retirement Support — Retirement support is framed as a standout component, highlighted by a 401(k) match described as 100% on the first 6% of base salary. This is positioned as a meaningful offset to less competitive cash compensation for some roles.
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Leave & Time Off Breadth — Leave and time off are portrayed as relatively robust, with references to multi-week vacation, paid holidays, sick time, and additional days tied to wellness or volunteering. This breadth is repeatedly treated as a tangible part of total rewards beyond base pay.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are presented as extensive, including the BeWell program, fitness discounts, onsite or supported health resources, and financial counseling. These offerings are depicted as strengthening the overall benefits proposition even when pay satisfaction is tepid.
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