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State StreetPosted 1 month ago

AI Systems Design Architect - Assistant Vice President

$90,000–$157,500 year

On-siteQuincy, Massachusetts, United States or Boston, Massachusetts, United States

Full TimeSenior LevelBachelors DegreeEnterprise

Job Summary

Own end-to-end system design for a major GenAI platform and shared AI services, translating business requirements into robust technical architectures across the AI stack. Define reference architectures, integration contracts, and non-functional requirements for model integration, orchestration, and downstream interactions. Partner with product, engineering, data science, and security teams to deliver enterprise-ready solutions leveraging cloud principles on AWS, Azure, or Google Cloud. Establish reusable patterns for RAG, model serving, and agentic workflows while ensuring alignment with Responsible AI, governance, and compliance standards. Conduct architecture reviews, technical design assessments, and proof-of-concept evaluations to guide trade-offs and standards adherence across pods.

Required Qualifications

  • Bachelor's degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline
  • 8–14 years of experience in solution architecture, enterprise application architecture, platform architecture, or AI/ML architecture
  • Strong 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 at least one major cloud platform: AWS, Azure, or Google Cloud Platform (GCP)
  • Strong understanding of cloud-native services including compute, storage, networking, identity and access management, security, and AI/ML services
  • Expertise in API architecture, microservices, distributed systems, event-driven architecture, and system integration patterns
  • Experience designing solutions with strong security, resiliency, scalability, observability, and performance considerations
  • Working knowledge of AI governance, Responsible AI, model risk, compliance, testing, and operational controls
  • Ability to lead architecture discussions and clearly communicate complex technical concepts to technical and business stakeholders
  • Strong collaboration, problem-solving, and stakeholder management skills

Desired Qualifications

  • Master's degree preferred

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