Architect Engineer, Data Platform Services

Salesforce•Seattle, WA

1d•$263,200 - $401,400•Hybrid

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 acting as the technical liaison for Salesforce's broader AI and data strategy. The role reports to the VP of Data Platform Services and collaborates with various internal teams, including product leadership and Customer Zero programs.

Requirements

Significant experience (typically 12-15+ years) in software or platform engineering 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/scalability patterns for enterprise-scale platforms.
Strong understanding of data platform architecture (lakehouse design, data catalog/governance, data contracts, metadata management) from a platform engineering perspective.
Experience shaping data platforms for AI/ML workloads, including data structure, governance, and serving for agentic or LLM consumption.
Hands-on familiarity with agent integration patterns (e.g., MCP) for connecting data systems to AI runtimes.
Fluency in agentic development patterns (development lifecycle, prompt/tool design, evaluation, deployment, observability).
Working understanding of how data platform decisions impact agent capabilities.
Strong grasp of the full product development lifecycle, from discovery to production operations.
Track record of setting engineering standards (data quality frameworks, automated data contracts, SLA enforcement) and building the culture/tooling for adoption.
Working knowledge of infrastructure-as-code, containerization (Kubernetes, Docker), and CI/CD in a cloud environment (AWS, GCP, or Azure).
Excellent written and verbal communication skills, able 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.

Nice To Haves

Experience operating within a data mesh or federated data organization.
Experience with semantic layer design and knowledge graph-based approaches for AI/analytics.
Background in enterprise data governance (attribute-based access control, data classification, regulatory compliance at scale).
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 discoverable, agent-ready assets, defining standards for automated data contracts, versioned schemas, and SLAs.
Set standards for how DPS teams design, build, and operate platform services, including API design, data contracts, reliability, observability, and secure 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 technical quality through shared design patterns, and represent DPS's technical vision to leadership.
Participate in Salesforce's Customer Zero programs, providing technical feedback on Data Cloud, Agentforce, and platform capabilities, and influencing the roadmap.