Senior Solution Architect - AI & Cloud Systems, Vice President

Who We Are Looking For

We are seeking an experienced, hands-on Solution Architect for AI and Cloud Systems to support State Street’s Anti-Money Laundering (AML) Compliance Technology team. In this role, you will partner with business, architecture, engineering, cybersecurity, risk, and infrastructure teams to design secure, scalable, resilient, and cost-effective AI and cloud solutions.

You will bring strong solution architecture expertise and practical experience in generative AI, agentic AI, AWS, Databricks, data platforms, and cloud-native application development.

• Lead the end-to-end architecture and design of enterprise AI, cloud, data, and application solutions.
• Translate business requirements into secure, scalable, resilient, and production-ready solution architectures.
• Define architecture patterns for generative AI, agentic AI, cloud-native applications, data integration, APIs, and event-driven systems.
• Provide architecture governance throughout the delivery lifecycle, from initial design through production rollout.
• Partner with engineering, cybersecurity, data, infrastructure, risk, and business teams to ensure solutions meet enterprise standards.
• Evaluate existing platforms and recommend modernization, performance, resiliency, and cost-optimization opportunities.
• Provide technical leadership and guidance to architects, developers, data engineers, and cloud engineers.

• Strong architecture leadership, critical thinking, problem-solving, and decision-making skills.
• Ability to translate complex business requirements into practical technology solutions.
• Strong communication and stakeholder management skills, including the ability to engage effectively with senior leaders.
• Experience driving architecture decisions across multiple teams and technology platforms.
• Ability to balance innovation, delivery speed, security, risk, operational resiliency, and cost.
• Strong understanding of architecture governance and technology-control requirements.
• Deep architecture and engineering expertise, with the ability to translate strategy into working solutions through design, prototyping, hands-on coding, and technical leadership across AI, cloud, and data platforms.

• Bachelor’s degree in computer science, engineering, information systems, or an equivalent combination of education and work experience.
• At least 10 years of overall technology experience, including significant experience in solution or enterprise architecture.
• Demonstrated experience architecting large-scale AI, cloud, data, and distributed application platforms.
• Experience in financial services, banking, compliance, or another highly regulated industry is preferred.
• AWS, Databricks, AI/ML, Kubernetes, or enterprise architecture certifications are preferred.

• Develop current-state, target-state, and transition architectures aligned with business and technology strategies.
• Design secure, production-grade generative AI and agentic AI solutions, including RAG, AI agents, model integration, evaluation, observability, and guardrails.
• Define reusable architecture patterns for AWS, Databricks, APIs, microservices, event streaming, data platforms, and hybrid-cloud integration.
• Ensure solution designs address security, data privacy, availability, performance, disaster recovery, monitoring, and operational support.
• Guide engineering teams during design, implementation, architecture reviews, and production-readiness assessments.
• Evaluate technology products and vendors and recommend solutions based on business value, risk, scalability, and total cost of ownership.
• Mentor architects and engineers while promoting architecture standards and engineering best practices.

• Strong experience in enterprise solution architecture, cloud architecture, and distributed systems design.
• Hands-on knowledge of AWS services, including Bedrock, S3, EC2, Lambda, API Gateway, IAM, and PostgreSQL-based platforms.
• Strong understanding of Generative AI and Agentic AI architecture, including LLMs, RAG, vector databases, AI agents, model evaluation,…