Architect Engineer, Data Platform Services

Salesforce•San Francisco, CA

2d•Remote

About The Position

Salesforce is seeking a Distinguished Engineer to define and lead the technical strategy for the Data Platform Services (DPS) team. DPS is responsible for building and operating the data foundation that powers Salesforce's AI transformation, making trusted, governed, and semantically rich data available at the speed and scale required for AI products. This senior individual contributor role involves shaping the platform's evolution to support AI-native consumption patterns, setting engineering standards, and connecting platform capabilities to Salesforce's broader AI and data strategy. The role reports directly to the VP of Data Platform Services and collaborates with various internal teams, product leadership, and external customer programs.

Requirements

Significant experience in software or platform engineering (typically 12 to 15+ years) with demonstrated impact at the scope of a senior or principal IC.
Demonstrated ability to define and drive a multi-year technical strategy for a platform organization.
Deep expertise in distributed systems design, cloud-native platform architecture, and reliability and scalability patterns for enterprise-scale platform services.
Strong understanding of data platform architecture (lakehouse design, data catalog and governance, data contract frameworks, metadata management) from a platform engineering perspective.
Experience shaping how data platforms enable AI/ML workloads, including data structure, governance, and serving for agentic or LLM-based consumption.
Hands-on familiarity with agent integration patterns such as MCP or equivalent protocols.
Fluency in agentic development patterns, including the agent development lifecycle.
Working understanding of how data platform decisions shape agent capabilities.
Strong grasp of the full product development lifecycle, from discovery through production operations.
Track record of setting engineering standards (data quality frameworks, automated data contracts, SLA enforcement) and building the technical culture and tooling for adoption.
Working knowledge of infrastructure-as-code, containerization (Kubernetes, Docker), and CI/CD patterns in a cloud environment (AWS, GCP, or Azure).
Excellent written and verbal communication skills, including the ability to make complex architectural tradeoffs legible to engineering and executive audiences.
Ability to lead through influence, set direction without authority, build consensus, and hold teams to high standards through dialogue.

Nice To Haves

Experience operating within a data mesh or federated data organization.
Experience with semantic layer design and knowledge graph-based approaches.
Background in enterprise data governance (attribute-based access control, data classification, regulatory compliance frameworks).
Experience in a Customer Zero or product co-development capacity.
Familiarity with Salesforce platform capabilities (Data Cloud, Agentforce, MuleSoft, Tableau Next) from an operator or integration perspective.
BS/MS in Computer Science, Software Engineering, or a related technical discipline, or equivalent work experience.

Responsibilities

Define how the DPS platform evolves to support AI-native workloads, including data governance, enrichment, and surfacing for AI agents and LLM pipelines.
Own the technical vision for transforming raw datasets into high-fidelity, discoverable, and agent-ready assets, defining global standards for automated data contracts, versioned schemas, and enforceable SLAs.
Set standards for how DPS teams design, build, and operate platform services, including API design, data contracts, reliability, observability, and secure-by-default service ownership.
Lead the reliability and scalability strategy for DPS platform services, establishing architectural principles, SLO frameworks, and operational standards.
Serve as the authoritative technical voice in design reviews, cross-team architecture decisions, and long-range planning.
Invest in coaching PMTS and senior engineers, raise the technical quality of the organization, and represent DPS's technical vision to leadership.
Participate in Customer Zero programs, providing technical feedback on Data Cloud, Agentforce, and platform capabilities, and collaborating with Product teams to influence the roadmap.