Sr. Enterprise AI Data Architect
for section headings. Only include sections that have real specific content. We need to parse the posting.
We have:
- About The Team (maybe "About the role"? The posting includes "About The Team". Could map to "About the role"? The instruction: use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use those headings if content exists.
We have "About The Team" describing team. That's about the role/team. So we can put under About the role
with that paragraph.
We have "Role Summary" which is also about role. Could combine.
We have "Responsibilities" list.
We have "Qualifications" with Required and Preferred.
We have "Work Flexibility" (Schedule) maybe schedule.
We have "Base Salary Ranges" (Pay).
We have "Benefits" section.
We have "Commitment to Diversity, Equity, and Inclusion" (maybe not needed; it's boilerplate EEO; we should remove EEO/equal-opportunity boilerplate. So drop that.
We have "FINRA Requirements" (minor metadata) maybe drop.
We have "Placement within the range..." etc.
We need to preserve all substantive information, not invent.
We need to use - for any list of duties/requirements/benefits.
We need to use
for prose.
We must not repeat job title as heading.
We must not put Job ID/requisition numbers as headings.
We must remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions.
Thus we need to extract:
- About the role/team: paragraphs about T. Rowe Price mission, team description, role summary.
Let's extract relevant prose:
"At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident. We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity. Join us for the opportunity to grow and make a difference in ways that matter to you."
Then "About The Team The Enterprise Data Architecture and Data Platform team is a central organization built to establish enterprise-wide standards and capabilities as scalable solutions to be used across the enterprise. This team defines and manages enterprise data architectures and AI data readiness working with Enterprise Architecture that ensures consistency, scale, controls and compliance to how data is managed. This organization is also responsible for enterprise capabilities including vendor solutions as product owners."
Then "Role Summary As a Senior Enterprise AI Data Architect, you will lead the design, governance, and evolution of enterprise data and AI architecture capabilities across the firm. This role is responsible for defining reference architectures, guiding implementation patterns, and ensuring scalable, secure, and governed solutions that enable enterprise data and AI outcomes. The ideal candidate brings deep expertise in modern cloud data platforms, AI/ML architecture, and enterprise integration patterns, along with strong communication and stakeholder management skills. This is a highly hands-on, full-stack architecture role spanning data ingestion, transformation, semantic and consumption layers, model orchestration, application integration, and production deployment patterns. The role includes both strategic architecture leadership and practical execution, including prototyping and proof-of-concept development to validate new capabilities. We are seeking an energetic, creative, and technically strong architect who enjoys solving complex enterprise problems and building reusable frameworks, standards, and patterns that scale data and AI capabilities across the organization."
We can combine these into a few paragraphs under About the role.
Next Responsibilities: list bullet points.
Responsibilities list:
- Lead the architecture, design, and selective hands-on implementation of enterprise data and AI solutions from concept through production.
- Define end-to-end architecture patterns covering data ingestion, transformation, semantic modeling, retrieval, model orchestration, inference, integration, and deployment.
- Build prototypes and proof-of-concepts to validate architecture decisions, evaluate emerging technologies, and accelerate adoption of new data and AI capabilities.
- Establish reusable design patterns for agentic, analytical, and model-driven workflows using cloud-native and enterprise data platforms.
- Design and guide integration of AI capabilities with enterprise applications, APIs, and data platforms such as Snowflake.
- Partner with engineering teams to ensure architecture patterns are implemented in a scalable, secure, and supportable manner.
- Define standards for metadata, lineage, governance, observability, and lifecycle management across data and AI solutions.
- Evaluate tradeoffs across tools, models, platforms, and integration approaches, and recommend solutions aligned to enterprise strategy and business needs.
- Collaborate with cross-functional teams to align architecture, platform capabilities, and delivery roadmaps.
- Drive adoption of enterprise architecture standards, reusable frameworks, and best practices across data and AI initiatives.
We'll put each as
- .
Next Qualifications: Required and Preferred.
Required list:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
- 8+ years of experience in data, platform, or solution architecture, including experience designing and delivering enterprise-scale cloud data and AI solutions.
- Hands-on experience with generative AI, machine learning, or advanced analytics solutions, including at least one use case delivered end-to-end into production.
- Strong experience with AWS and Snowflake, including architecture and implementation patterns for governed data access, analytics, and AI integration; experience with Amazon Bedrock Agent Core and Snowflake Cortex strongly preferred.
- Deep understanding of modern data architecture, including data ingestion, transformation, semantic modeling, metadata, lineage, data quality, governance, and production deployment patterns.
- Strong technical skills in Python or another modern programming language, along with experience in APIs, orchestration patterns, CI/CD, infrastructure as code, and operational best practices.
- Strong communication and stakeholder management skills, with the ability to influence architecture decisions, work across technical and business teams, and operate effectively in a fast-evolving environment.
Preferred list:
- A Bachelor's or Master's degree in a technical, 5 years of experiences working in Asset Management or a related financial services or highly regulated industry.
- AWS certified AI practitioner.
- SnowPro Core Certification.
Note: The preferred bullet seems garbled: "A Bachelor's or Master's degree in a technical, 5 years of experiences working in Asset Management or a related financial services or highly regulated industry." Probably means: Bachelor's or Master's degree in a technical field, plus 5 years experience in asset management etc. We'll keep as is.
We'll put Required under
Qualifications
maybe separate Required and Preferred? The instruction only lists Qualifications as a heading; we can include both required and preferred under that heading, maybe separate subheadings? But we should not invent headings not listed. Could just list all qualifications (required and preferred) as a list, maybe with notes. But better to separate required and preferred using or ? Not required to follow exactly; we can include both under Qualifications.
We'll output:
Qualifications
Required:
...
Preferred:
...
That's acceptable.
Next Benefits: list bullet points.
Benefits list:
- Competitive compensation
- Annual bonus eligibility
- A generous retirement plan
- Hybrid work schedule
- Health and wellness benefits, including online therapy
- Paid time off for vacation, illness, medical appointments, and volunteering days
- Family care resources, including fertility and adoption benefits
- Learn More About Our Benefits. (maybe not needed as it's a link; we can drop as it's instructional.)
We'll include those as - .
Next Pay: Base Salary Ranges.
We have multiple ranges based on location.
We need to include Pay section only if posting actually states them. Yes.
We should present the ranges clearly.
We can do:
Pay
Base salary ranges (based on location):
- $121,000.00 – $206,000.00 for Maryland, Colorado, Washington and remote workers
- $133,000.00 – $227,000.00 for Washington, D.C.
- $151,000.00 – $258,000.00 for New York, California
Placement within the range is based on individual’s relevant experience and skills. Base salary is only one component of total compensation; employees may be eligible for a discretionary bonus based on company and individual performance.
That's preserving info.
Next Schedule: Work Flexibility.
We have: "This role is eligible for hybrid work, with up to three days per week from home."
We can put under Schedule.
Schedule
Hybrid work eligible: up to three days per week from home.
We should not include "Work Flexibility" heading; we use Schedule.
Now we need to ensure we don't include any boilerplate like EEO, FINRA, etc.
We also need to remove duplicated lines.
Check for any duplicated content: The "About The Team" and "Role Summary" maybe overlapping but we keep.
Now produce HTML fragment.
We must not include or tags.
We'll output:
About the role
...
Responsibilities
...
Qualifications
Required:
...
Preferred:
...
Benefits
...
Pay
...
...
...
Schedule
...
Make sure to escape any HTML special characters? Not needed.
Now craft the prose for About the role.
Combine the three paragraphs into maybe two paragraphs.
Paragraph 1: T. Rowe Price mission description.
Paragraph 2: About the team and role summary.
Let's write:
At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident. We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity. Join us for the opportunity to grow and make a difference in ways that matter to you.
The Enterprise Data Architecture and Data Platform team is a central organization built to establish enterprise-wide standards and capabilities as scalable solutions to be used across the enterprise. This team defines and manages enterprise data architectures and AI data readiness working with Enterprise Architecture that ensures consistency, scale, controls and compliance
About the role
with that paragraph. We have "Role Summary" which is also about role. Could combine. We have "Responsibilities" list. We have "Qualifications" with Required and Preferred. We have "Work Flexibility" (Schedule) maybe schedule. We have "Base Salary Ranges" (Pay). We have "Benefits" section. We have "Commitment to Diversity, Equity, and Inclusion" (maybe not needed; it's boilerplate EEO; we should remove EEO/equal-opportunity boilerplate. So drop that. We have "FINRA Requirements" (minor metadata) maybe drop. We have "Placement within the range..." etc. We need to preserve all substantive information, not invent. We need to use- for any list of duties/requirements/benefits.
We need to use
for prose. We must not repeat job title as heading. We must not put Job ID/requisition numbers as headings. We must remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Thus we need to extract: - About the role/team: paragraphs about T. Rowe Price mission, team description, role summary. Let's extract relevant prose: "At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident. We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity. Join us for the opportunity to grow and make a difference in ways that matter to you." Then "About The Team The Enterprise Data Architecture and Data Platform team is a central organization built to establish enterprise-wide standards and capabilities as scalable solutions to be used across the enterprise. This team defines and manages enterprise data architectures and AI data readiness working with Enterprise Architecture that ensures consistency, scale, controls and compliance to how data is managed. This organization is also responsible for enterprise capabilities including vendor solutions as product owners." Then "Role Summary As a Senior Enterprise AI Data Architect, you will lead the design, governance, and evolution of enterprise data and AI architecture capabilities across the firm. This role is responsible for defining reference architectures, guiding implementation patterns, and ensuring scalable, secure, and governed solutions that enable enterprise data and AI outcomes. The ideal candidate brings deep expertise in modern cloud data platforms, AI/ML architecture, and enterprise integration patterns, along with strong communication and stakeholder management skills. This is a highly hands-on, full-stack architecture role spanning data ingestion, transformation, semantic and consumption layers, model orchestration, application integration, and production deployment patterns. The role includes both strategic architecture leadership and practical execution, including prototyping and proof-of-concept development to validate new capabilities. We are seeking an energetic, creative, and technically strong architect who enjoys solving complex enterprise problems and building reusable frameworks, standards, and patterns that scale data and AI capabilities across the organization." We can combine these into a few paragraphs under About the role. Next Responsibilities: list bullet points. Responsibilities list: - Lead the architecture, design, and selective hands-on implementation of enterprise data and AI solutions from concept through production. - Define end-to-end architecture patterns covering data ingestion, transformation, semantic modeling, retrieval, model orchestration, inference, integration, and deployment. - Build prototypes and proof-of-concepts to validate architecture decisions, evaluate emerging technologies, and accelerate adoption of new data and AI capabilities. - Establish reusable design patterns for agentic, analytical, and model-driven workflows using cloud-native and enterprise data platforms. - Design and guide integration of AI capabilities with enterprise applications, APIs, and data platforms such as Snowflake. - Partner with engineering teams to ensure architecture patterns are implemented in a scalable, secure, and supportable manner. - Define standards for metadata, lineage, governance, observability, and lifecycle management across data and AI solutions. - Evaluate tradeoffs across tools, models, platforms, and integration approaches, and recommend solutions aligned to enterprise strategy and business needs. - Collaborate with cross-functional teams to align architecture, platform capabilities, and delivery roadmaps. - Drive adoption of enterprise architecture standards, reusable frameworks, and best practices across data and AI initiatives. We'll put each as
- .
Next Qualifications: Required and Preferred.
Required list:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
- 8+ years of experience in data, platform, or solution architecture, including experience designing and delivering enterprise-scale cloud data and AI solutions.
- Hands-on experience with generative AI, machine learning, or advanced analytics solutions, including at least one use case delivered end-to-end into production.
- Strong experience with AWS and Snowflake, including architecture and implementation patterns for governed data access, analytics, and AI integration; experience with Amazon Bedrock Agent Core and Snowflake Cortex strongly preferred.
- Deep understanding of modern data architecture, including data ingestion, transformation, semantic modeling, metadata, lineage, data quality, governance, and production deployment patterns.
- Strong technical skills in Python or another modern programming language, along with experience in APIs, orchestration patterns, CI/CD, infrastructure as code, and operational best practices.
- Strong communication and stakeholder management skills, with the ability to influence architecture decisions, work across technical and business teams, and operate effectively in a fast-evolving environment.
Preferred list:
- A Bachelor's or Master's degree in a technical, 5 years of experiences working in Asset Management or a related financial services or highly regulated industry.
- AWS certified AI practitioner.
- SnowPro Core Certification.
Note: The preferred bullet seems garbled: "A Bachelor's or Master's degree in a technical, 5 years of experiences working in Asset Management or a related financial services or highly regulated industry." Probably means: Bachelor's or Master's degree in a technical field, plus 5 years experience in asset management etc. We'll keep as is.
We'll put Required under
Qualifications
maybe separate Required and Preferred? The instruction only lists Qualifications as a heading; we can include both required and preferred under that heading, maybe separate subheadings? But we should not invent headings not listed. Could just list all qualifications (required and preferred) as a list, maybe with notes. But better to separate required and preferred usingor ? Not required to follow exactly; we can include both under Qualifications. We'll output:
Qualifications
Required:
- ...
Preferred:
- ...
- . Next Pay: Base Salary Ranges. We have multiple ranges based on location. We need to include Pay section only if posting actually states them. Yes. We should present the ranges clearly. We can do:
Pay
Base salary ranges (based on location):
- $121,000.00 – $206,000.00 for Maryland, Colorado, Washington and remote workers
- $133,000.00 – $227,000.00 for Washington, D.C.
- $151,000.00 – $258,000.00 for New York, California
Placement within the range is based on individual’s relevant experience and skills. Base salary is only one component of total compensation; employees may be eligible for a discretionary bonus based on company and individual performance.
That's preserving info. Next Schedule: Work Flexibility. We have: "This role is eligible for hybrid work, with up to three days per week from home." We can put under Schedule.Schedule
Hybrid work eligible: up to three days per week from home.
We should not include "Work Flexibility" heading; we use Schedule. Now we need to ensure we don't include any boilerplate like EEO, FINRA, etc. We also need to remove duplicated lines. Check for any duplicated content: The "About The Team" and "Role Summary" maybe overlapping but we keep. Now produce HTML fragment. We must not include or tags. We'll output:About the role
...
Responsibilities
- ...
Qualifications
Required:
- ...
Preferred:
- ...
Benefits
- ...
Pay
...
- ...
...
Schedule
...
Make sure to escape any HTML special characters? Not needed. Now craft the prose for About the role. Combine the three paragraphs into maybe two paragraphs. Paragraph 1: T. Rowe Price mission description. Paragraph 2: About the team and role summary. Let's write:At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident. We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity. Join us for the opportunity to grow and make a difference in ways that matter to you.
The Enterprise Data Architecture and Data Platform team is a central organization built to establish enterprise-wide standards and capabilities as scalable solutions to be used across the enterprise. This team defines and manages enterprise data architectures and AI data readiness working with Enterprise Architecture that ensures consistency, scale, controls and compliance
- . Next Pay: Base Salary Ranges. We have multiple ranges based on location. We need to include Pay section only if posting actually states them. Yes. We should present the ranges clearly. We can do: