Architect Engineer, Data Platform Services

Job Category Software Engineering About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. About The Role Data Platform Services (DPS) is engineering the data foundation that powers Salesforce's AI transformation. We build and operate the platforms that make trusted, governed, and semantically rich data available at the speed and scale that Agentforce and next-generation AI products demand. Our work spans the full data lifecycle — from ingestion and lakehouse architecture to data-as-a-product (DaaP), quality, observability, and agent-ready context delivery — and our platform is consumed by Salesforce's largest internal business units every day. What You'll Do AI Readiness Strategy. Define how the DPS platform evolves to support AI-native workloads — including how data is governed, enriched, and surfaced for reliable consumption by AI agents and LLM pipelines. Data-as-a-Product Platform. Own the technical vision for transforming raw datasets into high-fidelity, discoverable, and agent-ready assets. This means defining the global standards for automated data contracts, versioned schemas, and enforceable SLAs. Your goal is to build the self-service infrastructure that allows domain teams to ship data with the same rigor, quality, and observability as a production microservice — ensuring that every data product in the DPS catalog is trusted by default. Engineering Standards & Architecture. Set the standards governing how DPS teams design, build, and operate platform services — API design, data contracts, reliability, observability, and secure-by-default service ownership — and drive adoption across the organization. Platform Reliability & Scale. Lead the reliability and scalability strategy for DPS platform services, establishing the architectural principles, SLO frameworks, and operational standards that govern platform performance at enterprise scale. Technical Leadership. Serve as the authoritative technical voice across design reviews, cross-team architecture decisions, and long-range planning — surfacing tradeoffs clearly, resolving cross-organizational dependencies, and partnering with Engineering Directors to connect technical investment to business outcomes. Engineering Multiplier. Invest in coaching PMTS and senior engineers across DPS, raise the technical quality of the organization through shared design patterns and written proposals, and represent DPS's technical vision to CDO leadership and peer platform teams. Customer Zero. Participate in Salesforce's Customer Zero programs — providing structured technical feedback on Data Cloud, Agentforce, and platform capabilities from the perspective of an enterprise-scale internal operator, and collaborating with Salesforce Product teams to influence the roadmap. What We're Looking For Required Significant experience in software or platform engineering — typically 12 to 15+ years — with demonstrated impact at the scope of a senior or principal IC: owning technical direction across multiple teams, shaping multi-year roadmaps, and influencing engineering outcomes at an organizational level. Demonstrated ability to define and drive a multi-year technical strategy for a platform organization — not just contribute to it, but own it and make it legible and actionable for engineering and business audiences. Deep expertise in distributed systems design, cloud-native platform architecture, and the reliability and scalability patterns that govern enterprise-scale platform services. Strong understanding of data platform architecture — including lakehouse design, data catalog and governance, data contract frameworks, and metadata management — from a platform engineering perspective. Experience shaping how data platforms enable AI/ML workloads — including how data is structured, governed, and served for agentic or LLM-based consumption — and hands‑on familiarity with agent integration patterns such as MCP or equivalent protocols for connecting data systems to AI runtimes. Fluency in agentic development patterns — including the agent development lifecycle from prompt and tool design through evaluation, deployment, and observability — and a working understanding of how data platform decisions shape what agents can reliably do. Paired with a strong grasp of the full product development lifecycle, from early discovery through production operations, with the ability to hold both perspectives simultaneously. Track record of setting engineering standards — including data quality frameworks, automated data contracts, and SLA enforcement — and building the technical culture and tooling that makes those standards easy to adopt across teams. 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 both engineering and executive audiences. Ability to lead through influence — comfortable setting direction without authority, building consensus, and holding teams to high standards through dialogue. Preferred Experience operating within a data mesh or federated data organization, where platform services and domain-owned data products coexist. Experience with semantic layer design and knowledge graph-based approaches to enriching data for AI and analytics consumption. Background in enterprise data governance — including attribute-based access control, data classification, and regulatory compliance frameworks at scale. Experience in a Customer Zero or product co-development capacity — working directly with a vendor's product team to influence the roadmap based on real operational experience. 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. The Right Fit This role is for someone who thinks at the intersection of platform engineering, AI readiness, and technical strategy — and who has the credibility and communication skills to move organizations toward a shared technical vision. You will be most effective here if you: Skills Can articulate a three-year platform strategy and still care deeply about whether the API Design is right. Are as comfortable writing a proposal for CDO leadership as you are reviewing a service design with a senior engineer. See data governance, semantic enrichment, and observability as foundational AI infrastructure — not compliance overhead. Have strong opinions about what makes a platform trustworthy and scalable, and can back those opinions with data and engineering rationale. Operate with extreme ownership — you see gaps and close them, whether that means writing the spec, reviewing the design, or escalating to the right person. Accommodations If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $218,400 - $365,200 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $263,200 - $401,400 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable. #J-18808-Ljbffr Salesforce