AI Systems Design Architect - Assistant Vice President
State Street · Quincy, MA · 1 mo ago
Art & Creative$90k–$158k/yrFull-time
We need to output HTML fragment with sections: About the role? Actually the posting includes description before responsibilities. We need to use for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include a section only when posting has real specific content. We have content for About the role? The initial paragraph: "We are seeking an AI System Design Architect (AVP) with strong expertise...". That's about the role. So we can have
for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include a section only when posting has real specific content. We have content for About the role? The initial paragraph: "We are seeking an AI System Design Architect (AVP) with strong expertise...". That's about the role. So we can have About the role
with that paragraph.
Responsibilities: there is a list under "Key Responsibilities". We'll put Responsibilities
then - each bullet.
Requirements: The posting has "Required Qualifications". That's qualifications. Also there is "Bachelor’s degree..." etc. That's qualifications. Also maybe "Skills"? The posting includes many skill items but they are within qualifications. We could separate Skills section if there is explicit skills list. The posting includes "Strong hands-on experience with Generative AI, LLMs, ML systems, RAG architectures, vector databases, and AI application integration." etc. That's more qualifications. We could treat "Required Qualifications" as Qualifications section. There's no separate Skills heading. We could still create Skills if we extract skill bullets, but better to follow instruction: only include sections when posting has real specific content. We have qualifications content. We could also have a Skills section if we want to separate but not required. Safer to include Qualifications only.
Pay: Salary Range $90,000 - $157,500 Annual. So we include Pay section.
Benefits: The posting includes benefits description: "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." So we include Benefits section.
Schedule: Not mentioned. So omit Schedule.
We must not include Job ID etc. Also remove boilerplate like Equal Opportunity etc. Also remove navigation etc. Also remove "About State Street" etc? That's boilerplate? It's about the company, maybe not required. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "About State Street" paragraph is not exactly boilerplate but could be considered company description; but it's not part of role specifics. Might be considered boilerplate? It's generic. Safer to omit it. Also remove "As an Equal Opportunity Employer..." etc. Also remove "Job Application Disclosure". Also remove "Read our CEO Statement". Also remove "Discover more information on jobs at StateStreet.com/careers". Also remove "Job ID: R-795374". Also remove "Salary Range $90,000 - $157,500 Annual The 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." That's part of Pay but includes extra location note. We should keep the salary range but can omit the extra sentence? The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. The extra sentence about location is substantive? It's about the range applicability. Might be considered part of Pay details. We could keep it as part of Pay section. But we need to avoid filler like "not specified". This is specific. So include.
Thus Pay section:
Salary Range $90,000 - $157,500 Annual. The 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.
Benefits section: list of benefits. Could be - ... each benefit. The paragraph includes semicolons. We can split into list items: 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); eligibility for certain tax advantaged savings plans.
We'll make each as
- .
Now Responsibilities: list bullets from "Key Responsibilities". Let's extract:
- Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
- Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
- Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
- Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
- Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
- Establish reusable architecture patterns for RAG, model serving, prompt workflows, agentic AI workflows, and AI application integration.
- Ensure alignment with Responsible AI, model governance, data handling, compliance, testing, risk, and production control requirements.
- Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases and platform capabilities.
- Review solution designs across pods and provide guidance on architecture decisions, trade-offs, and standards adherence.
- Partner with engineering and DevSecOps teams to support production readiness, release architecture, monitoring, and scalability planning.
We'll put each as
- .
Qualifications: The "Required Qualifications" paragraph includes multiple sentences. We can break into list items? The instruction: Use
- for any list of duties/requirements/benefits. So we should convert qualifications into list. Let's extract each qualification:
- 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 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.
We'll put each as
- .
About the role: The initial paragraph: "We are seeking an AI System Design Architect (AVP) with strong expertise in Generative AI, Machine Learning, enterprise architecture, cloud platforms, and scalable solution design. This role will own end-to-end system design for a major GenAI platform and shared AI services, ensuring solutions are secure, resilient, compliant, and aligned with enterprise architecture standards. The ideal candidate will translate business and platform requirements into robust technical architectures across the AI stack, define architecture patterns and integration contracts, establish non-functional requirements, and provide architecture reviews across pods. This role requires close collaboration with product, engineering, data science, cloud, and control teams to drive scalable, production-grade AI solutions."
We'll put that as
maybe multiple paragraphs but we can keep as one
.
Now ensure we don't repeat job title as heading. We are not.
Now output HTML fragment only.
Let's craft:
About the role
We are seeking an AI System Design Architect (AVP) with strong expertise in Generative AI, Machine Learning, enterprise architecture, cloud platforms, and scalable solution design. This role will own end-to-end system design for a major GenAI platform and shared AI services, ensuring solutions are secure, resilient, compliant, and aligned with enterprise architecture standards. The ideal candidate will translate business and platform requirements into robust technical architectures across the AI stack, define architecture patterns and integration contracts, establish non-functional requirements, and provide architecture reviews across pods. This role requires close collaboration with product, engineering, data science, cloud, and control teams to drive scalable, production-grade AI solutions.
Responsibilities
- Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
- Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
- Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
- Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
- Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
- Establish reusable architecture patterns for RAG, model serving, prompt workflows, agentic AI workflows, and AI application integration.
- Ensure alignment with Responsible AI, model governance, data handling, compliance, testing, risk, and production control requirements.
- Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases and platform capabilities.
- Review solution designs across pods and provide guidance on architecture decisions, trade-offs, and standards adherence.
- Partner with engineering and DevSecOps teams to support production readiness, release architecture, monitoring, and scalability planning.
Qualifications
- 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 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.
Benefits
- 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
Salary Range $90,000 - $157,500 Annual. The 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.
Benefits section: list of benefits. Could be- ... each benefit. The paragraph includes semicolons. We can split into list items: 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); eligibility for certain tax advantaged savings plans. We'll make each as
- . Now Responsibilities: list bullets from "Key Responsibilities". Let's extract: - Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions. - Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area. - Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs. - Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems. - Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness. - Establish reusable architecture patterns for RAG, model serving, prompt workflows, agentic AI workflows, and AI application integration. - Ensure alignment with Responsible AI, model governance, data handling, compliance, testing, risk, and production control requirements. - Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases and platform capabilities. - Review solution designs across pods and provide guidance on architecture decisions, trade-offs, and standards adherence. - Partner with engineering and DevSecOps teams to support production readiness, release architecture, monitoring, and scalability planning. We'll put each as
- .
Qualifications: The "Required Qualifications" paragraph includes multiple sentences. We can break into list items? The instruction: Use
- for any list of duties/requirements/benefits. So we should convert qualifications into list. Let's extract each qualification: - 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 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. We'll put each as
- .
About the role: The initial paragraph: "We are seeking an AI System Design Architect (AVP) with strong expertise in Generative AI, Machine Learning, enterprise architecture, cloud platforms, and scalable solution design. This role will own end-to-end system design for a major GenAI platform and shared AI services, ensuring solutions are secure, resilient, compliant, and aligned with enterprise architecture standards. The ideal candidate will translate business and platform requirements into robust technical architectures across the AI stack, define architecture patterns and integration contracts, establish non-functional requirements, and provide architecture reviews across pods. This role requires close collaboration with product, engineering, data science, cloud, and control teams to drive scalable, production-grade AI solutions."
We'll put that as
maybe multiple paragraphs but we can keep as one
. Now ensure we don't repeat job title as heading. We are not. Now output HTML fragment only. Let's craft:
About the role
We are seeking an AI System Design Architect (AVP) with strong expertise in Generative AI, Machine Learning, enterprise architecture, cloud platforms, and scalable solution design. This role will own end-to-end system design for a major GenAI platform and shared AI services, ensuring solutions are secure, resilient, compliant, and aligned with enterprise architecture standards. The ideal candidate will translate business and platform requirements into robust technical architectures across the AI stack, define architecture patterns and integration contracts, establish non-functional requirements, and provide architecture reviews across pods. This role requires close collaboration with product, engineering, data science, cloud, and control teams to drive scalable, production-grade AI solutions.
Responsibilities
- Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
- Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
- Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
- Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
- Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
- Establish reusable architecture patterns for RAG, model serving, prompt workflows, agentic AI workflows, and AI application integration.
- Ensure alignment with Responsible AI, model governance, data handling, compliance, testing, risk, and production control requirements.
- Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases and platform capabilities.
- Review solution designs across pods and provide guidance on architecture decisions, trade-offs, and standards adherence.
- Partner with engineering and DevSecOps teams to support production readiness, release architecture, monitoring, and scalability planning.
Qualifications
- 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 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.
Benefits
- 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