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

Salesforce

Quick summary

Work type
On-site
Location
San Francisco, CANew York, NYSeattle, WAIndianapolis, IN
Salary
$148,500–$260,100 / yr
Posted
8 days ago
Nearby
99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $174k
This role $204k
$122k most similar roles pay here $275k

This role pays more than 63% of similar roles. Most pay $136,750–$211,200 — the shaded band above. At the midpoint, this role pays about $204k versus about $174k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 127 open roles on FindRole.

Listed pay typically runs $171,200–$260,100 across 107 roles with salary data.

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At a glance

TL;DR · Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

Role Posting Log in to save

Join Salesforce’s Enterprise Knowledge Graph and AI Engineering team as a Senior Member of Technical Staff (SMTS) or Lead Member of Technical Staff (LMTS), where you will develop, optimize, and scale core knowledge graph components, semantic pipeline workflows, and AI-powered frameworks. The SMTS role focuses on hands-on coding to build production-ready systems, while the LMTS position involves leading design and implementation at an enterprise scale, including ontology engineering and strategic planning. Both roles require expertise in Python, distributed systems, cloud-native technologies like AWS or GCP, and graph databases such as Neo4j. You will work with semantic web concepts, develop AI tooling, and integrate data from various sources into the knowledge graph platform, ensuring robustness and scalability. Ideal candidates have extensive experience in software engineering, data integration, and a passion for advancing AI-driven solutions within an enterprise context.

Skills

Python Neo4j RDF/OWL SPARQL AWS GCP Azure GraphQL MCP frameworks Claude Cursor Windsurf GitHub Copilot Kafka SHACL CI/CD Semantic Web Knowledge Representation

What you'll do

  • Design and implement core knowledge graph components, focusing on performance and reliability.
  • Develop graph data models and semantic schemas to map structured and unstructured data to enterprise ontologies.
  • Write Python-based semantic routing frameworks to direct queries to appropriate knowledge graph indexes or vector databases.
  • Build AI-powered developer tools and automation platforms to improve engineering productivity and software quality.
  • Own the technical execution of specific platform features from concept through production deployment, ensuring adherence to standards.
  • Mentor engineers on the team, providing guidance in code reviews and design direction for technical rigor.

What we're looking for

  • 8+ years experience in software engineering, data engineering, or distributed systems (SMTS); 10+ years for LMTS.
  • Expert-level coding skills in Python and object-oriented/functional programming languages.
  • Hands-on experience with graph databases, semantic web concepts, and ontology modeling tools.
  • Proven ability to design and implement AI-powered developer tools and automation workflows.
  • Strong background in cloud-native system designs, microservices, and high-throughput event-driven systems.
  • Experience leading technical execution and mentoring mid-to-senior level engineers (LMTS).
  • Solid experience with semantic routing frameworks using Python for custom query handling.

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