Senior Solution Architect - AI & Cloud Systems, Vice President
State Street
Senior Solution Architect - AI & Cloud Systems, Vice President
Job Description
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. Salary Range: $120,000 - $202,500 AnnualThe range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary 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.About State StreetAcross the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.Discover more information on jobs at StateStreet.com/careersRead our CEO StatementJob Application Disclosure: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Locations
- Massachusetts, Quincy
- New Jersey, Princeton
Salary
120,000 - 202,500 USD / yearly
Skills Required
- solutionintermediate
- financial servicesintermediate
- enterprise solution architectureintermediate
- AWS servicesintermediate
- Pythonintermediate
- Databricksintermediate
- application securityintermediate
- AMLintermediate
- AI governanceintermediate
- LangChainintermediate
- Kafkaintermediate
Required Qualifications
- Bachelor’s degree in computer science, engineering, information systems, or an equivalent combination of education and work experience. (experience)
- Bachelor’s degree in computer science, engineering, information systems, or an equivalent combination of education and work experience. (experience)
- At least 10 years of overall technology experience, including significant experience in solution or enterprise architecture. (experience, 10 years)
- At least 10 years of overall technology experience, including significant experience in solution or enterprise architecture. (experience, 10 years)
- Demonstrated experience architecting large-scale AI, cloud, data, and distributed application platforms. (experience)
- Demonstrated experience architecting large-scale AI, cloud, data, and distributed application platforms. (experience)
- Experience in financial services, banking, compliance, or another highly regulated industry is preferred. (experience)
- Experience in financial services, banking, compliance, or another highly regulated industry is preferred. (experience)
- AWS, Databricks, AI/ML, Kubernetes, or enterprise architecture certifications are preferred. (certification)
- AWS, Databricks, AI/ML, Kubernetes, or enterprise architecture certifications are preferred. (certification)
- Strong experience in enterprise solution architecture, cloud architecture, and distributed systems design. (experience)
- Strong experience in enterprise solution architecture, cloud architecture, and distributed systems design. (experience)
- Hands-on knowledge of AWS services, including Bedrock, S3, EC2, Lambda, API Gateway, IAM, and PostgreSQL-based platforms. (experience)
- Hands-on knowledge of AWS services, including Bedrock, S3, EC2, Lambda, API Gateway, IAM, and PostgreSQL-based platforms. (experience)
- Strong understanding of Generative AI and Agentic AI architecture, including LLMs, RAG, vector databases, AI agents, model evaluation, observability, and guardrails. (experience)
- Strong understanding of Generative AI and Agentic AI architecture, including LLMs, RAG, vector databases, AI agents, model evaluation, observability, and guardrails. (experience)
- Experience with Python, APIs, microservices, containers, Kubernetes, and event-driven architecture. (experience)
- Experience with Python, APIs, microservices, containers, Kubernetes, and event-driven architecture. (experience)
- Familiarity with Databricks, data lakes, lakehouse architecture, data pipelines, and enterprise data integration. (experience)
- Familiarity with Databricks, data lakes, lakehouse architecture, data pipelines, and enterprise data integration. (experience)
- Knowledge of application security, identity and access management, encryption, resiliency, disaster recovery, and cloud governance. (experience)
- Knowledge of application security, identity and access management, encryption, resiliency, disaster recovery, and cloud governance. (experience)
- Understanding of DevSecOps, CI/CD, infrastructure as code, automated testing, and production monitoring practices. (experience)
- Understanding of DevSecOps, CI/CD, infrastructure as code, automated testing, and production monitoring practices. (experience)
- Proven ability to communicate architecture decisions, technical risks, alternatives, and recommendations to senior stakeholders. (experience)
- Proven ability to communicate architecture decisions, technical risks, alternatives, and recommendations to senior stakeholders. (experience)
Preferred Qualifications
- Experience with AML, compliance, risk management, or other financial-services technology platforms. (experience)
- Experience with AML, compliance, risk management, or other financial-services technology platforms. (experience)
- Knowledge of AI governance, responsible AI, model risk management, and data privacy controls. (experience)
- Knowledge of AI governance, responsible AI, model risk management, and data privacy controls. (experience)
- Experience with LangChain, LangGraph, Strands, CrewAI, Pydantic, or similar AI frameworks. (experience)
- Experience with LangChain, LangGraph, Strands, CrewAI, Pydantic, or similar AI frameworks. (experience)
- Familiarity with Kafka, Apache Airflow, Terraform, OpenShift, and cloud cost-management practices. (experience)
- Familiarity with Kafka, Apache Airflow, Terraform, OpenShift, and cloud cost-management practices. (experience)
- Experience modernizing legacy applications and migrating enterprise workloads to the cloud. (experience)
- Experience modernizing legacy applications and migrating enterprise workloads to the cloud. (experience)
Responsibilities
- Lead the end-to-end architecture and design of enterprise AI, cloud, data, and application solutions.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Provide technical leadership and guidance to architects, developers, data engineers, and cloud engineers.
- Develop current-state, target-state, and transition architectures aligned with business and technology strategies.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Mentor architects and engineers while promoting architecture standards and engineering best practices.
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