AI Systems Design Architect, Assistant Vice President

State Street

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Quincy, MA
Salary: $90,000–$157,500 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $180k

This role $124k

$74k $237k

below market most similar roles pay here above market

This role pays less than 83% of similar roles. Most pay $139,220–$221,425 — the blue band above. At the midpoint, this role pays about $124k versus about $180k for comparable roles.

Based on 240 similar postings.

Employer

About State Street

State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody

State Street currently has 353 open roles on FindRole.

Listed pay typically runs $117,500–$192,972 across 202 roles with salary data.

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At a glance

TL;DR · AI Systems Design Architect, Assistant Vice President

Role Posting Log in to save

The AI Systems Design Architect - Assistant Vice President will join the team to own end-to-end system design for a major Generative AI platform and shared AI services. This role involves translating business requirements into robust technical architectures, defining integration contracts, and establishing non-functional requirements for the AI stack. You will build scalable, secure, and resilient solutions including RAG architectures, model serving, prompt workflows, and agentic AI workflows. Key responsibilities include conducting architecture reviews, managing model governance, and ensuring compliance with Responsible AI standards. You must demonstrate expertise in Generative AI, LLMs, vector databases, and cloud platforms like AWS, Azure, or Google Cloud. The role requires deep knowledge of microservices, distributed systems, API architecture, and cloud-native services to solve complex enterprise AI integration problems.

Skills

Generative AI Machine Learning LLMs RAG AWS Azure Google Cloud Platform Vector Databases Microservices Distributed Systems Event-Driven Architecture API Architecture DevSecOps Model Governance Responsible AI System Design Cloud-Native Services

What you'll do

Own end-to-end system design for a major GenAI platform including model integration, orchestration, and data flows.
Translate business and product requirements into scalable, secure, and maintainable AI solution designs.
Define reference architectures, design standards, integration contracts, and non-functional requirements for the platform.
Establish reusable architecture patterns for RAG, model serving, prompt workflows, and agentic AI workflows.
Design cloud-native solutions on AWS, Azure, or GCP ensuring interoperability, scalability, and operational readiness.
Ensure all designs align with Responsible AI, model governance, data handling, and compliance requirements.
Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases.
Review solution designs across pods to provide guidance on architecture decisions and trade-offs.

What we're looking for

Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline.
Master’s degree (preferred).
8–14 years of experience in solution, enterprise application, platform, or AI/ML architecture.
Hands-on experience with Generative AI, LLMs, ML systems, RAG architectures, vector databases, and AI application integration.
Proven experience in cloud architecture and solution design on AWS, Azure, or Google Cloud Platform.
Expertise in API architecture, microservices, distributed systems, event-driven architecture, and system integration patterns.
Working knowledge of AI governance, Responsible AI, model risk, compliance, testing, and operational controls.
Ability to lead architecture discussions and communicate complex technical concepts to technical and business stakeholders.

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