Manager, Data Architecture & AI Enablement
for each heading. Use - for any list of duties/requirements/benefits. Use
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Preserve all substantive info. Include a section only when posting has real specific content. Avoid filler like "commensurate with experience", "not specified", etc. So we need to extract content.
Let's parse posting:
First paragraph: "What happens when your architecture becomes the backbone of enterprise strategy? If you have five or more years of hands-on data architecture and engineering experience on Databricks and Azure — plus real delivery with AI patterns like retrieval-augmented generation and document intelligence - we want to speak with you! We are seeking a Manager, Data Architecture & AI Enablement, to join our AI & Data Center of Excellence in Richmond, VA. with a hybrid work schedule. Relocation benefits will be provided."
That's about the role: location, hybrid schedule, relocation benefits.
Next: "In this role, you will own the target-state data architecture for Laboratory Services, Regulatory Affairs, R&D, and Product Innovation, while delivering governed, production-ready AI capabilities for scientists and regulatory professionals. As part of the AI & Data Center of Excellence, you will define and execute the architecture for functions historically outside the enterprise data strategy, ensuring scalable, compliant data and AI solutions in a highly regulated environment. Combining data architecture and AI enablement, you will drive integration, data modeling, semantic layer, and data-readiness decisions; establish retrieval, document intelligence, and conversational AI patterns; and ensure data is not only delivered but also adopted through AI capabilities actively used in production."
That's responsibilities.
Then "What you’ll be doing:" bullet list:
- Own the target-state data architecture for these domains — source integration, layered models, and the curated semantic layer that serves analytics and AI.
- Lead source discovery and integration across LIMS, SDMS, electronic lab notebooks, regulatory information management, quality management and product lifecycle systems, plus SharePoint and file-based sources.
- Design the data models and semantics for studies, samples, methods, results, specifications, formulations and submissions, using conformed dimensions, controlled vocabularies and consistent units of measure.
- Deliver AI enablement: document intelligence over scientific and regulatory content, retrieval-augmented generation, governed conversational access, and the evaluation and monitoring that keep it trustworthy.
- Build and oversee production pipelines on Databricks and Azure — medallion layering with Delta, change data capture, schema evolution, observability and cost management.
- Govern these domains in Unity Catalog and Microsoft Purview, aligned to Microsoft Entra ID groups and Azure role assignments, so access, lineage and cataloging are enforced once.
- Design for a regulated environment: validation, audit trails, versioned transformations, data quality rules as code, and responsible AI standards for every model and agent released.
- Lead and coach a small team of architects and engineers, and set the design, code and acceptance standards that onshore and offshore delivery partners build to.
- Work forward deployed with laboratory, regulatory and product teams, shipping working data products against real feedback rather than requirements documents.
Then "We want you to have:" bullet list:
- Bachelor's degree in Computer Science, Information Systems, Engineering, a physical or life science, or a related technical field.
- 5+ years of hands-on data architecture and data engineering experience, with a portfolio of pipelines and data models you personally designed and built.
- Hands-on integration experience with laboratory and regulatory systems: LIMS, SDMS, electronic lab notebooks, regulatory information management platforms, quality management systems such as TrackWise, and product lifecycle or product data management tools.
- Strong command of the Databricks/Microsoft data and AI stack: Azure Data Factory, Azure Data Lake Storage Gen2, Microsoft Entra ID and Azure RBAC, Microsoft Purview, and Azure AI or Microsoft Fabric services.
- Practical delivery experience with modern AI patterns: retrieval-augmented generation, embeddings and vector retrieval, document intelligence over unstructured content, agentic and conversational access to curated data, and the data readiness and evaluation work underneath them.
Then "The starting salary is based on but not limited to experience, knowledge, and qualifications in determining compensation decisions. The Salary Range for this position is: $137,500.00 - $199,450.00."
That's Pay.
Then "Why You’ll Love Building Your Career at Altria" bullet list of benefits:
- Work where connection and flexibility meet — enjoy the benefits of in-person collaboration three days a week (Tuesday - Thursday), while maintaining the flexibility to work remotely on Mondays and Fridays. Our hybrid approach empowers you to stay connected, collaborate with colleagues, and manage your schedule in a way that works best for you.
- Own your time — start with 15 days of paid time off, 13 paid holidays, 2 floating holiday days, and a 37.5-hour workweek so you can recharge and live fully.
- A place where you belong — where your ideas are welcomed, your growth is encouraged, and your impact is real.
- Get recognized for your work — annual merit increases and performance bonus.
- A future you can count on — 401(k) matching from day one; plus Deferred Profit Sharing, an annual company contribution in an amount equal to 13%–17% of your base salary.
- Help with your goals — get help with student loan repayment assistance, attend a conference, or gain a new certification with professional development stipends.
- Support for what matters most — comprehensive medical, dental, and vision coverage for you and your family.
- Celebrating your milestones — paid parental and bonding leave for life’s biggest moments.
- Wellness that goes beyond work — programs that care for your whole well-being at whatever stage you are in your life.
- A culture that gives back — paid volunteer days and a shared commitment to making a difference.
- At Altria, we offer more than benefits — we offer a career that fits your life, rewards your ambition, and celebrates your impact.
Also "This position is not eligible for sponsorship." That's maybe a note but not a benefit; could be included in a short p.
We need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule.
We need to decide what goes where.
About the role: maybe the introductory paragraph describing role, location, hybrid schedule, relocation benefits.
Responsibilities: the "In this role, you will ..." plus the "What you’ll be doing:" bullet list.
Requirements: maybe the "We want you to have:" bullet list (education, experience). Could split into Requirements (experience) and Qualifications (education) and Skills (technical). But we need to follow instruction: Use sections only when posting has real specific content. We can have multiple sections.
We have:
- About the role: location, hybrid schedule, relocation benefits.
- Responsibilities: description and bullet list.
- Requirements: maybe the 5+ years experience etc? Actually that's also qualification.
- Qualifications: Bachelor's degree etc.
- Skills: Databricks/Azure stack, AI patterns.
- Benefits: the "Why You’ll Love Building Your Career at Altria" bullet list.
- Pay: salary range.
- Schedule: hybrid work schedule (maybe mention 3 days in office, 2 remote). Already covered in About the role but we could separate.
We must not repeat job title as heading. Also not include Job ID etc.
We must not include filler like "commensurate with experience". Not present.
We need to output only HTML fragment, no /, no markdown fences.
We'll produce something like:
About the role
We are seeking a Manager, Data Architecture & AI Enablement to join our AI & Data Center of Excellence in Richmond, VA. The role offers a hybrid work schedule (three days in‑office, two days remote) and relocation benefits.
Responsibilities
In this role, you will own the target‑state data architecture for Laboratory Services, Regulatory Affairs, R&D, and Product Innovation while delivering governed, production‑ready AI capabilities for scientists and regulatory professionals. You will define and execute architecture for functions historically outside the enterprise data strategy, ensuring scalable, compliant data and AI solutions in a highly regulated environment. You will drive integration, data modeling, semantic layer, and data‑readiness decisions; establish retrieval, document intelligence, and conversational AI patterns; and ensure data is delivered and adopted through AI capabilities actively used in production.
- Own the target‑state data architecture for these domains — source integration, layered models, and the curated semantic layer that serves analytics and AI.
- Lead source discovery and integration across LIMS, SDMS, electronic lab notebooks, regulatory information management, quality management and product lifecycle systems, plus SharePoint and file‑based sources.
- Design the data models and semantics for studies, samples, methods, results, specifications, formulations and submissions, using conformed dimensions, controlled vocabularies and consistent units of measure.
- Deliver AI enablement: document intelligence over scientific and regulatory content, retrieval‑augmented generation, governed conversational access, and the evaluation and monitoring that keep it trustworthy.
- Build and oversee production pipelines on Databricks and Azure — medallion layering with Delta, change data capture, schema evolution, observability and cost management.
- Govern these domains in Unity Catalog and Microsoft Purview, aligned to Microsoft Entra ID groups and Azure role assignments, so access, lineage and cataloging are enforced once.
- Design for a regulated environment: validation, audit trails, versioned transformations, data quality rules as code, and responsible AI standards for every model and agent released.
- Lead and coach a small team of architects and engineers, and set the design, code and acceptance standards that onshore and offshore delivery partners build to.
- Work forward deployed with laboratory, regulatory and product teams, shipping working data products against real feedback rather than requirements documents.
Requirements
- 5+ years of hands‑on data architecture and data engineering experience, with a portfolio of pipelines and data models you personally designed and built.
Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, a physical or life science, or a related technical field.
Skills
- Hands‑on integration experience with laboratory and regulatory systems: LIMS, SDMS, electronic lab notebooks, regulatory information management platforms, quality management systems such as TrackWise, and product lifecycle or product data management tools.
- Strong command of the Databricks/Microsoft data and AI stack: Azure Data Factory, Azure Data Lake Storage Gen2, Microsoft Entra ID and Azure RBAC, Microsoft Purview, and Azure AI or Microsoft Fabric services.
- Practical delivery experience with modern AI patterns: retrieval‑augmented generation, embeddings and vector retrieval, document intelligence over unstructured content, agentic and conversational access to curated data, and the data readiness and evaluation work underneath them.
Benefits
- Work where connection and flexibility meet — enjoy the benefits of in‑person collaboration three days a week (Tuesday‑Thursday), while maintaining the flexibility to work remotely on Mondays and Fridays.
- Own your time — start with 15 days of paid time off, 13 paid holidays, 2 floating holiday days, and a 37.5‑hour workweek.
- A place where you belong — where your ideas are welcomed, your growth is encouraged, and your impact is real.
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Preserve all substantive info. Include a section only when posting has real specific content. Avoid filler like "commensurate with experience", "not specified", etc. So we need to extract content. Let's parse posting: First paragraph: "What happens when your architecture becomes the backbone of enterprise strategy? If you have five or more years of hands-on data architecture and engineering experience on Databricks and Azure — plus real delivery with AI patterns like retrieval-augmented generation and document intelligence - we want to speak with you! We are seeking a Manager, Data Architecture & AI Enablement, to join our AI & Data Center of Excellence in Richmond, VA. with a hybrid work schedule. Relocation benefits will be provided." That's about the role: location, hybrid schedule, relocation benefits. Next: "In this role, you will own the target-state data architecture for Laboratory Services, Regulatory Affairs, R&D, and Product Innovation, while delivering governed, production-ready AI capabilities for scientists and regulatory professionals. As part of the AI & Data Center of Excellence, you will define and execute the architecture for functions historically outside the enterprise data strategy, ensuring scalable, compliant data and AI solutions in a highly regulated environment. Combining data architecture and AI enablement, you will drive integration, data modeling, semantic layer, and data-readiness decisions; establish retrieval, document intelligence, and conversational AI patterns; and ensure data is not only delivered but also adopted through AI capabilities actively used in production." That's responsibilities. Then "What you’ll be doing:" bullet list: - Own the target-state data architecture for these domains — source integration, layered models, and the curated semantic layer that serves analytics and AI. - Lead source discovery and integration across LIMS, SDMS, electronic lab notebooks, regulatory information management, quality management and product lifecycle systems, plus SharePoint and file-based sources. - Design the data models and semantics for studies, samples, methods, results, specifications, formulations and submissions, using conformed dimensions, controlled vocabularies and consistent units of measure. - Deliver AI enablement: document intelligence over scientific and regulatory content, retrieval-augmented generation, governed conversational access, and the evaluation and monitoring that keep it trustworthy. - Build and oversee production pipelines on Databricks and Azure — medallion layering with Delta, change data capture, schema evolution, observability and cost management. - Govern these domains in Unity Catalog and Microsoft Purview, aligned to Microsoft Entra ID groups and Azure role assignments, so access, lineage and cataloging are enforced once. - Design for a regulated environment: validation, audit trails, versioned transformations, data quality rules as code, and responsible AI standards for every model and agent released. - Lead and coach a small team of architects and engineers, and set the design, code and acceptance standards that onshore and offshore delivery partners build to. - Work forward deployed with laboratory, regulatory and product teams, shipping working data products against real feedback rather than requirements documents. Then "We want you to have:" bullet list: - Bachelor's degree in Computer Science, Information Systems, Engineering, a physical or life science, or a related technical field. - 5+ years of hands-on data architecture and data engineering experience, with a portfolio of pipelines and data models you personally designed and built. - Hands-on integration experience with laboratory and regulatory systems: LIMS, SDMS, electronic lab notebooks, regulatory information management platforms, quality management systems such as TrackWise, and product lifecycle or product data management tools. - Strong command of the Databricks/Microsoft data and AI stack: Azure Data Factory, Azure Data Lake Storage Gen2, Microsoft Entra ID and Azure RBAC, Microsoft Purview, and Azure AI or Microsoft Fabric services. - Practical delivery experience with modern AI patterns: retrieval-augmented generation, embeddings and vector retrieval, document intelligence over unstructured content, agentic and conversational access to curated data, and the data readiness and evaluation work underneath them. Then "The starting salary is based on but not limited to experience, knowledge, and qualifications in determining compensation decisions. The Salary Range for this position is: $137,500.00 - $199,450.00." That's Pay. Then "Why You’ll Love Building Your Career at Altria" bullet list of benefits: - Work where connection and flexibility meet — enjoy the benefits of in-person collaboration three days a week (Tuesday - Thursday), while maintaining the flexibility to work remotely on Mondays and Fridays. Our hybrid approach empowers you to stay connected, collaborate with colleagues, and manage your schedule in a way that works best for you. - Own your time — start with 15 days of paid time off, 13 paid holidays, 2 floating holiday days, and a 37.5-hour workweek so you can recharge and live fully. - A place where you belong — where your ideas are welcomed, your growth is encouraged, and your impact is real. - Get recognized for your work — annual merit increases and performance bonus. - A future you can count on — 401(k) matching from day one; plus Deferred Profit Sharing, an annual company contribution in an amount equal to 13%–17% of your base salary. - Help with your goals — get help with student loan repayment assistance, attend a conference, or gain a new certification with professional development stipends. - Support for what matters most — comprehensive medical, dental, and vision coverage for you and your family. - Celebrating your milestones — paid parental and bonding leave for life’s biggest moments. - Wellness that goes beyond work — programs that care for your whole well-being at whatever stage you are in your life. - A culture that gives back — paid volunteer days and a shared commitment to making a difference. - At Altria, we offer more than benefits — we offer a career that fits your life, rewards your ambition, and celebrates your impact. Also "This position is not eligible for sponsorship." That's maybe a note but not a benefit; could be included in a short p. We need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide what goes where. About the role: maybe the introductory paragraph describing role, location, hybrid schedule, relocation benefits. Responsibilities: the "In this role, you will ..." plus the "What you’ll be doing:" bullet list. Requirements: maybe the "We want you to have:" bullet list (education, experience). Could split into Requirements (experience) and Qualifications (education) and Skills (technical). But we need to follow instruction: Use sections only when posting has real specific content. We can have multiple sections. We have: - About the role: location, hybrid schedule, relocation benefits. - Responsibilities: description and bullet list. - Requirements: maybe the 5+ years experience etc? Actually that's also qualification. - Qualifications: Bachelor's degree etc. - Skills: Databricks/Azure stack, AI patterns. - Benefits: the "Why You’ll Love Building Your Career at Altria" bullet list. - Pay: salary range. - Schedule: hybrid work schedule (maybe mention 3 days in office, 2 remote). Already covered in About the role but we could separate. We must not repeat job title as heading. Also not include Job ID etc. We must not include filler like "commensurate with experience". Not present. We need to output only HTML fragment, no /, no markdown fences. We'll produce something like:
About the role
We are seeking a Manager, Data Architecture & AI Enablement to join our AI & Data Center of Excellence in Richmond, VA. The role offers a hybrid work schedule (three days in‑office, two days remote) and relocation benefits.
Responsibilities
In this role, you will own the target‑state data architecture for Laboratory Services, Regulatory Affairs, R&D, and Product Innovation while delivering governed, production‑ready AI capabilities for scientists and regulatory professionals. You will define and execute architecture for functions historically outside the enterprise data strategy, ensuring scalable, compliant data and AI solutions in a highly regulated environment. You will drive integration, data modeling, semantic layer, and data‑readiness decisions; establish retrieval, document intelligence, and conversational AI patterns; and ensure data is delivered and adopted through AI capabilities actively used in production.
- Own the target‑state data architecture for these domains — source integration, layered models, and the curated semantic layer that serves analytics and AI.
- Lead source discovery and integration across LIMS, SDMS, electronic lab notebooks, regulatory information management, quality management and product lifecycle systems, plus SharePoint and file‑based sources.
- Design the data models and semantics for studies, samples, methods, results, specifications, formulations and submissions, using conformed dimensions, controlled vocabularies and consistent units of measure.
- Deliver AI enablement: document intelligence over scientific and regulatory content, retrieval‑augmented generation, governed conversational access, and the evaluation and monitoring that keep it trustworthy.
- Build and oversee production pipelines on Databricks and Azure — medallion layering with Delta, change data capture, schema evolution, observability and cost management.
- Govern these domains in Unity Catalog and Microsoft Purview, aligned to Microsoft Entra ID groups and Azure role assignments, so access, lineage and cataloging are enforced once.
- Design for a regulated environment: validation, audit trails, versioned transformations, data quality rules as code, and responsible AI standards for every model and agent released.
- Lead and coach a small team of architects and engineers, and set the design, code and acceptance standards that onshore and offshore delivery partners build to.
- Work forward deployed with laboratory, regulatory and product teams, shipping working data products against real feedback rather than requirements documents.
Requirements
- 5+ years of hands‑on data architecture and data engineering experience, with a portfolio of pipelines and data models you personally designed and built.
Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, a physical or life science, or a related technical field.
Skills
- Hands‑on integration experience with laboratory and regulatory systems: LIMS, SDMS, electronic lab notebooks, regulatory information management platforms, quality management systems such as TrackWise, and product lifecycle or product data management tools.
- Strong command of the Databricks/Microsoft data and AI stack: Azure Data Factory, Azure Data Lake Storage Gen2, Microsoft Entra ID and Azure RBAC, Microsoft Purview, and Azure AI or Microsoft Fabric services.
- Practical delivery experience with modern AI patterns: retrieval‑augmented generation, embeddings and vector retrieval, document intelligence over unstructured content, agentic and conversational access to curated data, and the data readiness and evaluation work underneath them.
Benefits
- Work where connection and flexibility meet — enjoy the benefits of in‑person collaboration three days a week (Tuesday‑Thursday), while maintaining the flexibility to work remotely on Mondays and Fridays.
- Own your time — start with 15 days of paid time off, 13 paid holidays, 2 floating holiday days, and a 37.5‑hour workweek.
- A place where you belong — where your ideas are welcomed, your growth is encouraged, and your impact is real.