Salesforce

1 month ago

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Develop and scale Salesforce’s Enterprise Knowledge Graph and AI pipelines as a senior engineer and technical lead. You will design graph data models, build production-grade semantic routing, and create AI-powered tooling, partnering with Principal/Lead Engineers, Product Management, Ontology experts, and Data Engineering teams to turn high-level visions into scalable, reliable, enterprise-grade foundations across AI-driven experiences.

Location: San Francisco, New York, Seattle, Indianapolis

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design & implement core knowledge graph platform components, focusing on performance, throughput, reliability, high availability, and data integrity.
•Develop graph data models, write complex graph queries, and build scalable data pipelines mapping structured/unstructured data to enterprise ontologies and taxonomies.
•Create and maintain Python-based semantic routing frameworks to parse and dynamically direct queries to knowledge graph indexes or vector databases.
•Build, integrate, and optimize AI-powered developer tooling and automation platforms (Claude, Cursor, Windsurf, MCP) for engineering productivity.
•Collaborate with Lead/Principal Engineers, Product Management, Ontology experts, and Data Engineering teams to translate high-level visions into production-ready systems.

Pay and Benefits

Salary: USD 148,500 - 260,100 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityRemote WorkPaid Leave

Key Requirements

•8+ years hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
•Strong Python proficiency and object-oriented/functional programming.
•Experience designing/building Knowledge Graph platforms, ontologies, semantic models, taxonomies, or enterprise metadata management systems.
•Solid experience with graph databases (e.g., Neo4j, RDF/OWL) and mapping data to structured taxonomies.
•Distributed cloud-native systems experience (AWS, GCP, or Azure) with microservices, REST/gRPC, and event-driven data streaming (Kafka).

Experience:8+ yearsEnterprise data platformsGraph databasesAIKnowledge GraphPythonCloud

Education:Bachelor's

Skills:PythonGraph databasesNeo4jRDF/OWLSPARQLOntologiesSemantic modelsTaxonomyK8s?Kafka

Languages:English

Tech Stack:PythonNeo4jRDF/OWLSPARQLKafkaAWSGCPAzure

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: 4.1

Website LinkedIn Glassdoor

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Salesforce

1 month ago

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Seattle, Indianapolis

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design & implement core knowledge graph platform components, focusing on performance, throughput, reliability, high availability, and data integrity.
•Develop graph data models, write complex graph queries, and build scalable data pipelines mapping structured/unstructured data to enterprise ontologies and taxonomies.
•Create and maintain Python-based semantic routing frameworks to parse and dynamically direct queries to knowledge graph indexes or vector databases.
•Build, integrate, and optimize AI-powered developer tooling and automation platforms (Claude, Cursor, Windsurf, MCP) for engineering productivity.
•Collaborate with Lead/Principal Engineers, Product Management, Ontology experts, and Data Engineering teams to translate high-level visions into production-ready systems.

Pay and Benefits

Salary: USD 148,500 - 260,100 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityRemote WorkPaid Leave

Key Requirements

•8+ years hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
•Strong Python proficiency and object-oriented/functional programming.
•Experience designing/building Knowledge Graph platforms, ontologies, semantic models, taxonomies, or enterprise metadata management systems.
•Solid experience with graph databases (e.g., Neo4j, RDF/OWL) and mapping data to structured taxonomies.
•Distributed cloud-native systems experience (AWS, GCP, or Azure) with microservices, REST/gRPC, and event-driven data streaming (Kafka).

Experience:8+ yearsEnterprise data platformsGraph databasesAIKnowledge GraphPythonCloud

Education:Bachelor's

Skills:PythonGraph databasesNeo4jRDF/OWLSPARQLOntologiesSemantic modelsTaxonomyK8s?Kafka

Languages:English

Tech Stack:PythonNeo4jRDF/OWLSPARQLKafkaAWSGCPAzure

Company Brief

Salesforce

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: 4.1

Website LinkedIn Glassdoor