Salesforce, Inc..
Overview
Salesforce is seeking a visionary, innovative, and deeply technical Principal Architect to lead the architectural strategy and design for Salesforce’s enterprise data, AI/ML, and automation platforms. Reporting to Salesforce’s Chief Data Officer, this VP-level architect will own the entire data and ML/AI platform architecture and its seamless integration across all other platform and application domains at Salesforce. As Salesforce builds the first agentic enterprise, a cohesive, scalable, and intelligent data architecture is more critical than ever before to enable humans and agents to deliver success together. This pivotal role is the single-threaded architectural owner responsible for the blueprint of our entire enterprise data ecosystem. This leader will drive the technical strategy to power data activations, automations, agents, and analytics across the enterprise with a trusted, resilient, and flexible architecture. They will ensure our architecture is robust, scalable, and forward-looking, capable of processing billions of events per day and providing new capabilities to Salesforce through technologies like vector databases, graph databases, ontology systems, unstructured data processing, LLM model distillation, and much more. This is a unique opportunity to shape the future of data and AI at Salesforce, driving significant business impact and innovation at scale. Your Impact & Responsibilities
Architectural Vision & Strategy:
Define and champion a compelling long-term technical vision for Salesforce’s unified data, analytics, ML/AI, and automation platforms. Ensure the architecture is aligned with the overall company strategy, customer needs, and the development of Salesforce’s product roadmap. Technical Roadmap & Execution:
Develop and manage a multi-year architectural roadmap delivering with peer product and engineering leaders. Guide the organization in making critical technology choices and drive the end-to-end technical design for data platforms, analytics systems, ML/AI infrastructure, and automation systems. Platform Design & Development:
Lead the design of highly scalable, distributed, transactional data platforms on cloud infrastructure, particularly AWS. Provide architectural guidance to a large, integrated team of product managers, engineers, and data scientists. Drive thoughtful architectural decisions on data management, analytical data processing, customer data platforms, LLMs, vector and graph databases, and agentic development models. Cross-Functional Leadership:
Serve as a key collaborator and technical authority for engineering, data science, product, and business unit teams across the company. Build strong relationships and influence effectively with stakeholders at all levels of a global, matrixed organization to ensure architectural alignment and success. Stakeholder Management:
Engage with executive leadership and key stakeholders to communicate complex architectural strategies, secure buy-in, and manage expectations. Translate business requirements into sound architectural solutions to enable product and engineering teams to build resilient and scalable solutions. Technical Mentorship & Development:
Build and mentor a community of senior technical talent within the organization. Foster an inspiring culture of innovation, technical excellence, and continuous improvement that helps everyone do the best work of their careers. Governance & Operational Excellence:
Drive operational excellence by implementing best practices for platform architecture, data modeling, and lifecycle management. Ensure architectural designs promote platform uptime, data quality, reliability, and adherence to data governance and privacy regulations. Industry Thought Leadership:
Represent Salesforce and its data and AI vision at technical conferences, customer engagements, and relevant industry forums. Required Qualifications
15-20+ years of experience in software architecture, design, and development, with at least 7-10 years in a Principal-level or VP-level architectural role focused on enterprise-scale data, AI, or technology platforms. Master’s or PhD in Computer Science, Engineering, Data Science, or a related technical field, or equivalent work experience. Proven track record of designing, building, and launching complex, data-intensive, transactional systems on cloud platforms (especially AWS) Deep, hands-on expertise with large-scale data platforms and technologies, including data lakes (e.g., AWS S3, Azure Data Lake), data warehouses (e.g., Snowflake, BigQuery, Redshift), columnar store databases and formats (e.g., Vertica, ClickHouse, Apache Parquet, ORC), and data processing engines (e.g., Apache Spark, Databricks, DBT). Deep expertise in modern data and AI architecture, including strong knowledge of LLMs, vector and graph databases, agentic development models, machine learning engineering, and ontology systems. Expert in Domain-Driven Design (DDD): Deep understanding and practical application of DDD principles to model complex business domains and design loosely coupled, highly cohesive systems. Proven ability to establish a ubiquitous language and collaborate with domain experts to create effective models. Microservices and Event-Driven Architecture: Extensive experience designing and implementing microservices architectures and event-driven systems. Modern Software Development Practices: A strong advocate for and practitioner of modern software development methodologies, including Agile, Scrum, and Kanban. Deep experience with CI/CD (Continuous Integration/Continuous Delivery) pipelines, DevOps culture, and infrastructure-as-code (e.g., Terraform, CloudFormation). API Design and Management: Expertise in designing and managing robust, scalable, and secure APIs (REST, GraphQL). Understanding of API gateways, service meshes, and API lifecycle management best practices. Architectural Governance and Quality: Experience establishing and enforcing architectural best practices, coding standards, and design patterns. Proven ability to conduct architectural reviews and provide constructive feedback to engineering teams. Extremely strong data modeling skills and a deep understanding of data modeling and data architecture best practices. Exceptional strategic thinking and problem-solving skills, with a demonstrated ability to synthesize complex technical concepts into a clear architectural vision. Outstanding written and verbal communication skills with the ability to craft compelling technical narratives and present effectively to diverse audiences, including C-level executives and deep technical teams. Proven ability to work cross-functionally and influence effectively in a global, matrixed organization. Ability to travel domestically and internationally as needed (~15-25%). Preferred Qualifications
Deep technical expertise for Salesforce products and the Salesforce platform ecosystem, including Salesforce Data Cloud, Tableau, and MuleSoft, and Informatica. Experience with data governance, privacy regulations, and implementing ethical AI frameworks in practice through intelligent software engineering practices to ensure highly compliant and secure applications and data platforms. Active participation in the data & AI/ML research, open-source community, and industry events. Experience building or significantly contributing to enterprise products that incorporate machine learning and AI decision systems.
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Salesforce is seeking a visionary, innovative, and deeply technical Principal Architect to lead the architectural strategy and design for Salesforce’s enterprise data, AI/ML, and automation platforms. Reporting to Salesforce’s Chief Data Officer, this VP-level architect will own the entire data and ML/AI platform architecture and its seamless integration across all other platform and application domains at Salesforce. As Salesforce builds the first agentic enterprise, a cohesive, scalable, and intelligent data architecture is more critical than ever before to enable humans and agents to deliver success together. This pivotal role is the single-threaded architectural owner responsible for the blueprint of our entire enterprise data ecosystem. This leader will drive the technical strategy to power data activations, automations, agents, and analytics across the enterprise with a trusted, resilient, and flexible architecture. They will ensure our architecture is robust, scalable, and forward-looking, capable of processing billions of events per day and providing new capabilities to Salesforce through technologies like vector databases, graph databases, ontology systems, unstructured data processing, LLM model distillation, and much more. This is a unique opportunity to shape the future of data and AI at Salesforce, driving significant business impact and innovation at scale. Your Impact & Responsibilities
Architectural Vision & Strategy:
Define and champion a compelling long-term technical vision for Salesforce’s unified data, analytics, ML/AI, and automation platforms. Ensure the architecture is aligned with the overall company strategy, customer needs, and the development of Salesforce’s product roadmap. Technical Roadmap & Execution:
Develop and manage a multi-year architectural roadmap delivering with peer product and engineering leaders. Guide the organization in making critical technology choices and drive the end-to-end technical design for data platforms, analytics systems, ML/AI infrastructure, and automation systems. Platform Design & Development:
Lead the design of highly scalable, distributed, transactional data platforms on cloud infrastructure, particularly AWS. Provide architectural guidance to a large, integrated team of product managers, engineers, and data scientists. Drive thoughtful architectural decisions on data management, analytical data processing, customer data platforms, LLMs, vector and graph databases, and agentic development models. Cross-Functional Leadership:
Serve as a key collaborator and technical authority for engineering, data science, product, and business unit teams across the company. Build strong relationships and influence effectively with stakeholders at all levels of a global, matrixed organization to ensure architectural alignment and success. Stakeholder Management:
Engage with executive leadership and key stakeholders to communicate complex architectural strategies, secure buy-in, and manage expectations. Translate business requirements into sound architectural solutions to enable product and engineering teams to build resilient and scalable solutions. Technical Mentorship & Development:
Build and mentor a community of senior technical talent within the organization. Foster an inspiring culture of innovation, technical excellence, and continuous improvement that helps everyone do the best work of their careers. Governance & Operational Excellence:
Drive operational excellence by implementing best practices for platform architecture, data modeling, and lifecycle management. Ensure architectural designs promote platform uptime, data quality, reliability, and adherence to data governance and privacy regulations. Industry Thought Leadership:
Represent Salesforce and its data and AI vision at technical conferences, customer engagements, and relevant industry forums. Required Qualifications
15-20+ years of experience in software architecture, design, and development, with at least 7-10 years in a Principal-level or VP-level architectural role focused on enterprise-scale data, AI, or technology platforms. Master’s or PhD in Computer Science, Engineering, Data Science, or a related technical field, or equivalent work experience. Proven track record of designing, building, and launching complex, data-intensive, transactional systems on cloud platforms (especially AWS) Deep, hands-on expertise with large-scale data platforms and technologies, including data lakes (e.g., AWS S3, Azure Data Lake), data warehouses (e.g., Snowflake, BigQuery, Redshift), columnar store databases and formats (e.g., Vertica, ClickHouse, Apache Parquet, ORC), and data processing engines (e.g., Apache Spark, Databricks, DBT). Deep expertise in modern data and AI architecture, including strong knowledge of LLMs, vector and graph databases, agentic development models, machine learning engineering, and ontology systems. Expert in Domain-Driven Design (DDD): Deep understanding and practical application of DDD principles to model complex business domains and design loosely coupled, highly cohesive systems. Proven ability to establish a ubiquitous language and collaborate with domain experts to create effective models. Microservices and Event-Driven Architecture: Extensive experience designing and implementing microservices architectures and event-driven systems. Modern Software Development Practices: A strong advocate for and practitioner of modern software development methodologies, including Agile, Scrum, and Kanban. Deep experience with CI/CD (Continuous Integration/Continuous Delivery) pipelines, DevOps culture, and infrastructure-as-code (e.g., Terraform, CloudFormation). API Design and Management: Expertise in designing and managing robust, scalable, and secure APIs (REST, GraphQL). Understanding of API gateways, service meshes, and API lifecycle management best practices. Architectural Governance and Quality: Experience establishing and enforcing architectural best practices, coding standards, and design patterns. Proven ability to conduct architectural reviews and provide constructive feedback to engineering teams. Extremely strong data modeling skills and a deep understanding of data modeling and data architecture best practices. Exceptional strategic thinking and problem-solving skills, with a demonstrated ability to synthesize complex technical concepts into a clear architectural vision. Outstanding written and verbal communication skills with the ability to craft compelling technical narratives and present effectively to diverse audiences, including C-level executives and deep technical teams. Proven ability to work cross-functionally and influence effectively in a global, matrixed organization. Ability to travel domestically and internationally as needed (~15-25%). Preferred Qualifications
Deep technical expertise for Salesforce products and the Salesforce platform ecosystem, including Salesforce Data Cloud, Tableau, and MuleSoft, and Informatica. Experience with data governance, privacy regulations, and implementing ethical AI frameworks in practice through intelligent software engineering practices to ensure highly compliant and secure applications and data platforms. Active participation in the data & AI/ML research, open-source community, and industry events. Experience building or significantly contributing to enterprise products that incorporate machine learning and AI decision systems.
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