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**AI & Data Platform Architect - EY GDS** - **Role:** Design, assess, and evolve enterprise-scale AI platforms on cloud environments (Azure, AWS, or GCP) for US-based enterprise clients. - **Key Responsibilities:** Platform architecture & strategy, cloud & platform design, data & platform capabilities, AI & generative AI enablement, governance, security & responsible AI, measurement & outcomes. - **Required Experience:** Proven experience as a Platform Architect, AI Platform Architect, or similar role. Strong hands-on experience with Azure, AWS, or GCP, data warehouses, data lakes, and lakehouse architectures, as well as generative AI, machine learning, and deep learning platforms. - **Required Skills:** Bachelor’s or master’s degree in computer science, software engineering, or related field. Strong proficiency in SQL, Python, data analysis, data cloud solutions, and platform-level data modeling. Understands AI platform architecture patterns, data management, governance frameworks, and has hands-on knowledge of AI ready data implementations, ETL/ELT, processing, MDM, data quality, data lineage, LLMs, and RAG architecture. - **Location:** Buenos Aires, Argentina (Hybrid)
- Compensation
- Not specified
- City
- Not specified
- Country
- Argentina, United States
Currency: Not specified
Full Job Description
Job Description: AI & Data Platform Architect
- Location: Buenos Aires - Argentina (Hybrid)
- Clients: USbased Enterprise Clients
- Cloud: Azure, AWS, or GCP
About the Role
We are actively recruiting an accomplished AI & Data Platform Architect to join our team. This role is for a senior architect with deep experience designing, assessing, and evolving enterprisescale AI platforms on cloud environments.
The AI Platform Architect will work closely with client stakeholders to assess their current AI platform landscape and operating model, define northstar and transition platform architectures, and guide the implementation of scalable, secure, and governed AI platforms.
You will bring a consulting mindset, strong technical judgment, and flexibility to work across multiple cloud platforms and data management, governance, and AI technologies.
Key Responsibilities
Platform Architecture & Strategy
- Analyze and document currentstate AI platform architectures across enterprise domains.
- Define northstar, target, and transition platform architectures aligned to enterprise needs, AI use cases, and technology strategies.
- Provide architectural guidance and best practices that balance scalability, security, cost, and delivery velocity.
Cloud & Platform Design
- Design AI platforms on Azure, AWS, or GCP, evaluating:
- Compute, storage, and networking components
- Availability, scalability, elasticity, and fault tolerance
- Disaster recovery and business continuity
- Evaluate singlecloud and multicloud platform architectures based on enterprise standards and constraints.
Data & Platform Capabilities
- Define platform standards and best practices for:
- Data modeling and data management
- ETL/ELT pipelines
- Batch, nearrealtime, and realtime data processing
- Data serving and analytics enablement
- Design and guide implementation of Data Warehouse, Data Lake, and Lakehouse components as part of the AI platform.
AI & Generative AI Enablement
- Define and implement platform capabilities to support:
- Machine Learning and Deep Learning workloads
- Generative AI solutions
- LLMbased systems, including RAG (RetrievalAugmented Generation) patterns
- Cognitive flows and AIdriven applications
- Ensure AI platform components are productionready, scalable, and governed.
Governance, Security & Responsible AI
- Ensure platform designs comply with enterprise data governance, security, and privacy standards.
- Collaborate with governance teams on:
- Data cataloging and lineage
- Master Data Management (MDM)
- Metadata and data quality frameworks
- Embed Responsible AI, compliance, and ethical considerations into platform architecture.
Measurement & Outcomes
- Define and implement KPIs to measure:
- AI platform maturity and adoption
- Governance and security effectiveness
- Platform reliability, performance, and business value
Desired Experience
- Experience as a Platform Architect, AI Platform Architect, Solutions Architect, or similar role.
- Proven experience designing and implementing enterprise AI platforms in cloud environments.
- Strong handson experience with Azure, AWS, and/or GCP.
- Handson experience implementing:
- Data Warehouse, Data Lake, and Lakehouse architectures
- Analytics and AI platform components
- Handson experience with:
- Generative AI, Machine Learning, and Deep Learning platforms
- LLMbased architectures and cognitive flows
- (Nice to have) Experience creating dashboards, reports, and KPIs using tools such as Power BI or Tableau.
- Proven experience working with Data Cataloging, Data Lineage, and Master Data Management initiatives.
- Experience collaborating in multidisciplinary teams including data engineers, AI engineers, data scientists, governance teams, and business stakeholders.
- Prior experience supporting US enterprise clients is highly desirable.
Required Skills & Qualifications
- Bachelors or masters degree in computer science, Software Engineering, Data Science, Mathematics, or a related field.
- Strong proficiency in:
- SQL and Python
- Data analysis and data profiling
- Platformlevel data modeling and storage strategies
- Data cloud solutions (Azure, AWS, GCP)
- Strong understanding of:
- AI & Data platform architecture patterns (Lakehouse, Warehouse, Data Mesh, Data Factory, Data Vault)
- Data management and data governance frameworks.
- Handson knowledge of:
- AI Ready data implementations at scale
- ETL, ELT, Near real time processing
- MDM, Data Quality, Data Lineage.
- LLMs and Generative AI
- RAG architecture
- Excellent written and verbal communication skills, with the ability to communicate architectural decisions clearly to technical and nontechnical stakeholders.
- Strong awareness of compliance, ethics, and Responsible AI.
- A consulting mindset with the ability to adapt, learn, and apply new technologies quickly.
What Were Looking For
We are looking for passionate architects who are excited about building and evolving AI platforms at enterprise scale. You care deeply about platform quality, governance, and longterm sustainability, and you enjoy working across teams to turn complex AI ambitions into reliable, secure, and scalable platforms.
If this resonates with you, we strongly encourage you to apply.
SIMILAR OPPORTUNITIES
AI & Data Platform Architect - EY GDS
Compensation
Not specified
City: Not specified
Country: Argentina, United States
**AI & Data Platform Architect - EY GDS** - **Role:** Design, assess, and evolve enterprise-scale AI platforms on cloud environments (Azure, AWS, or GCP) for US-based enterprise clients. - **Key Responsibilities:** Platform architecture & strategy, cloud & platform design, data & platform capabilities, AI & generative AI enablement, governance, security & responsible AI, measurement & outcomes. - **Required Experience:** Proven experience as a Platform Architect, AI Platform Architect, or similar role. Strong hands-on experience with Azure, AWS, or GCP, data warehouses, data lakes, and lakehouse architectures, as well as generative AI, machine learning, and deep learning platforms. - **Required Skills:** Bachelor’s or master’s degree in computer science, software engineering, or related field. Strong proficiency in SQL, Python, data analysis, data cloud solutions, and platform-level data modeling. Understands AI platform architecture patterns, data management, governance frameworks, and has hands-on knowledge of AI ready data implementations, ETL/ELT, processing, MDM, data quality, data lineage, LLMs, and RAG architecture. - **Location:** Buenos Aires, Argentina (Hybrid)
Full Job Description
Job Description: AI & Data Platform Architect
- Location: Buenos Aires - Argentina (Hybrid)
- Clients: USbased Enterprise Clients
- Cloud: Azure, AWS, or GCP
About the Role
We are actively recruiting an accomplished AI & Data Platform Architect to join our team. This role is for a senior architect with deep experience designing, assessing, and evolving enterprisescale AI platforms on cloud environments.
The AI Platform Architect will work closely with client stakeholders to assess their current AI platform landscape and operating model, define northstar and transition platform architectures, and guide the implementation of scalable, secure, and governed AI platforms.
You will bring a consulting mindset, strong technical judgment, and flexibility to work across multiple cloud platforms and data management, governance, and AI technologies.
Key Responsibilities
Platform Architecture & Strategy
- Analyze and document currentstate AI platform architectures across enterprise domains.
- Define northstar, target, and transition platform architectures aligned to enterprise needs, AI use cases, and technology strategies.
- Provide architectural guidance and best practices that balance scalability, security, cost, and delivery velocity.
Cloud & Platform Design
- Design AI platforms on Azure, AWS, or GCP, evaluating:
- Compute, storage, and networking components
- Availability, scalability, elasticity, and fault tolerance
- Disaster recovery and business continuity
- Evaluate singlecloud and multicloud platform architectures based on enterprise standards and constraints.
Data & Platform Capabilities
- Define platform standards and best practices for:
- Data modeling and data management
- ETL/ELT pipelines
- Batch, nearrealtime, and realtime data processing
- Data serving and analytics enablement
- Design and guide implementation of Data Warehouse, Data Lake, and Lakehouse components as part of the AI platform.
AI & Generative AI Enablement
- Define and implement platform capabilities to support:
- Machine Learning and Deep Learning workloads
- Generative AI solutions
- LLMbased systems, including RAG (RetrievalAugmented Generation) patterns
- Cognitive flows and AIdriven applications
- Ensure AI platform components are productionready, scalable, and governed.
Governance, Security & Responsible AI
- Ensure platform designs comply with enterprise data governance, security, and privacy standards.
- Collaborate with governance teams on:
- Data cataloging and lineage
- Master Data Management (MDM)
- Metadata and data quality frameworks
- Embed Responsible AI, compliance, and ethical considerations into platform architecture.
Measurement & Outcomes
- Define and implement KPIs to measure:
- AI platform maturity and adoption
- Governance and security effectiveness
- Platform reliability, performance, and business value
Desired Experience
- Experience as a Platform Architect, AI Platform Architect, Solutions Architect, or similar role.
- Proven experience designing and implementing enterprise AI platforms in cloud environments.
- Strong handson experience with Azure, AWS, and/or GCP.
- Handson experience implementing:
- Data Warehouse, Data Lake, and Lakehouse architectures
- Analytics and AI platform components
- Handson experience with:
- Generative AI, Machine Learning, and Deep Learning platforms
- LLMbased architectures and cognitive flows
- (Nice to have) Experience creating dashboards, reports, and KPIs using tools such as Power BI or Tableau.
- Proven experience working with Data Cataloging, Data Lineage, and Master Data Management initiatives.
- Experience collaborating in multidisciplinary teams including data engineers, AI engineers, data scientists, governance teams, and business stakeholders.
- Prior experience supporting US enterprise clients is highly desirable.
Required Skills & Qualifications
- Bachelors or masters degree in computer science, Software Engineering, Data Science, Mathematics, or a related field.
- Strong proficiency in:
- SQL and Python
- Data analysis and data profiling
- Platformlevel data modeling and storage strategies
- Data cloud solutions (Azure, AWS, GCP)
- Strong understanding of:
- AI & Data platform architecture patterns (Lakehouse, Warehouse, Data Mesh, Data Factory, Data Vault)
- Data management and data governance frameworks.
- Handson knowledge of:
- AI Ready data implementations at scale
- ETL, ELT, Near real time processing
- MDM, Data Quality, Data Lineage.
- LLMs and Generative AI
- RAG architecture
- Excellent written and verbal communication skills, with the ability to communicate architectural decisions clearly to technical and nontechnical stakeholders.
- Strong awareness of compliance, ethics, and Responsible AI.
- A consulting mindset with the ability to adapt, learn, and apply new technologies quickly.
What Were Looking For
We are looking for passionate architects who are excited about building and evolving AI platforms at enterprise scale. You care deeply about platform quality, governance, and longterm sustainability, and you enjoy working across teams to turn complex AI ambitions into reliable, secure, and scalable platforms.
If this resonates with you, we strongly encourage you to apply.
SIMILAR OPPORTUNITIES
