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. 

What You Will Be Responsible For 

• 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. 

What We Value 

The following capabilities will help you succeed in this role: 

• 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. 

Education and Experience Qualifications 

• 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. 

Architecture and Design Responsibilities 

• 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. 

Required Skills and Experience 

• 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, observability, and guardrails. 

• Experience with Python, APIs, microservices, containers, Kubernetes, and event-driven architecture. 

• Familiarity with Databricks, data lakes, lakehouse architecture, data pipelines, and enterprise data integration. 

• Knowledge of application security, identity and access management, encryption, resiliency, disaster recovery, and cloud governance. 

• Understanding of DevSecOps, CI/CD, infrastructure as code, automated testing, and production monitoring practices. 

• Proven ability to communicate architecture decisions, technical risks, alternatives, and recommendations to senior stakeholders. 

Preferred Qualifications 

• Experience with AML, compliance, risk management, or other financial-services technology platforms. 

• Knowledge of AI governance, responsible AI, model risk management, and data privacy controls. 

• Experience with LangChain, LangGraph, Strands, CrewAI, Pydantic, or similar AI frameworks. 

• Familiarity with Kafka, Apache Airflow, Terraform, OpenShift, and cloud cost-management practices. 

• Experience modernizing legacy applications and migrating enterprise workloads to the cloud.