Software Engineering PMTS - Data Platform

Salesforce
San Francisco, Seattle
Workplace: OnsiteFull timeUSD 197,300 - 313,700 annuallyFunction: Software EngineeringExperience: 10+ yearsSkills: ["Executive communication","Cross-org leadership","Mentorship","Architecture governance","Stakeholder influence"]

Own the end-to-end data and intelligence architecture for AgentExchange, consolidating fragmented telemetry pipelines into a trusted platform. Define shared data contracts, streaming/batch ingestion standards, and reliability SLOs, and build self-service analytics and marketplace measurement dashboards. Lead ML and agentic layers with RAG, embeddings, vector stores, MCP-based data access, and evaluation harnesses—while setting governance, security, and privacy guardrails for LLM/agent surfaces. Represent the platform in cross-org architecture reviews and guide migrations and mentorship across the team.

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FursaFursa
Salesforce
Salesforce
2 days ago

Software Engineering PMTS - Data Platform

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Last checked: 2 hours agoStatus: Live

Job Summary

Own the end-to-end data and intelligence architecture for AgentExchange, consolidating fragmented telemetry pipelines into a trusted platform. Define shared data contracts, streaming/batch ingestion standards, and reliability SLOs, and build self-service analytics and marketplace measurement dashboards. Lead ML and agentic layers with RAG, embeddings, vector stores, MCP-based data access, and evaluation harnesses—while setting governance, security, and privacy guardrails for LLM/agent surfaces. Represent the platform in cross-org architecture reviews and guide migrations and mentorship across the team.
Location: San Francisco, Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Own end-to-end data architecture for the AgentExchange data platform, including canonical data model, destination consolidation, telemetry taxonomy, and roadmap.
  • •Design and enforce pipelines and data contracts across ingestion (streaming and batch), schema governance, and pipeline reliability SLOs.
  • •Build self-service analytics and partner-facing dashboards for GMV/attrition/install/search measurement and effort score frameworks.
  • •Architect the ML and agentic data layer, including feature store, training/serving infrastructure, monitoring, MCP-based agent access, RAG over corpora, and evaluation harnesses.
  • •Lead cross-org technical direction through architecture reviews (VAT), migration leadership, and mentorship for Data Engineering & Analytics.

Pay and Benefits

Salary: USD 197,300 - 313,700 annually
Perks:Health InsuranceDentalVision401kPaid ParentalLife InsuranceDisability InsuranceEquity

Key Requirements

  • •10+ years in software/data engineering, including multi-year ownership of an enterprise-scale data or ML platform.
  • •Deep architecture experience across at least three areas such as lakehouse/warehouse design, streaming + batch pipelines, dimensional/event modeling, feature stores, and model serving.
  • •Cloud-native data infrastructure experience with Snowflake, BigQuery, Redshift, or Databricks and AWS-based platforms.
  • •Production LLM systems experience including RAG, embeddings/vector stores, prompt/context engineering, evaluation (offline/online), and safety controls.
  • •Working knowledge of MCP or equivalent agent protocols, plus data security and governance including PII handling, multi-tenant isolation, fine-grained access, and GDPR/CCPA.
Experience:10+ years
Skills:Executive communicationCross-org leadershipMentorshipArchitecture governanceStakeholder influence
Tech Stack:SnowflakeBigQueryRedshiftDatabricksAWSLakehouseData warehouseStreamingBatch pipelinesDimensional modelingEvent modelingFeature storeModel servingRAGEmbeddingsVector storePrompt engineeringContext engineeringOffline evaluationOnline evaluation

Company Brief

Salesforce
Provides a leading cloud-based customer relationship management (CRM) platform with sales, service, marketing, analytics, and integration tools that empower businesses to manage customer relationships and digital transformation at scale.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 1999
Glassdoor
Glassdoor: 4.1
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