Senior Knowledge Graph Architect & AI Platform Lead

salesforce.com, inc.; Indianapolis (IN); On-site; USD 197,300 - 313,700; Full time

Benefits offered by this job

401(k) plan

Employee stock purchase program

Medical, dental, vision

Job summary

Salesforce is seeking a Principal Member of Technical Staff to lead the Enterprise Knowledge Graph strategy, including architecture, ontology-driven systems, and AI-powered tooling. You will partner with cross‑functional teams to drive scalable platforms and productivity benefits across engineering teams.

The role requires deep expertise in knowledge graph technologies, graph databases, and AI‑powered workflows, with a track record of delivering large-scale initiatives.

Qualifications

• 12+ years in software engineering, data engineering, distributed systems, or related fields.
• Proven experience defining and delivering enterprise-scale Knowledge Graph platforms with AI capabilities.
• Cloud-native architectures experience across AWS, GCP, or Azure with strong data governance.

Responsibilities

• Define long-term vision and roadmap for Salesforce's Enterprise Knowledge Graph platform.
• Lead architecture for knowledge graph ecosystems, semantic layers, and retrieval architectures.
• Drive AI-powered developer tooling and engineering automation to improve productivity and quality.
• Collaborate with Architecture, Product Management, Ontology, Data Engineering, and AI Platform teams to align investments.

Skills

Knowledge Graph

Graph databases

AI tooling

Enterprise data platforms

Distributed systems

Cloud platforms (AWS/GCP/Azure)

Leadership & stakeholders

Education

Related technical degree

Tools

Neo4j

TopQuadrant

RDF/OWL

SPARQL

Vector databases

Claude/Cursor/Windsurf

GitHub Copilot

Job description

Salesforce is seeking a Principal Member of Technical Staff to lead the Enterprise Knowledge Graph strategy, including architecture, ontology-driven systems, and AI-powered tooling. You will partner with cross‑functional teams to drive scalable platforms and productivity benefits across engineering teams.

The role requires deep expertise in knowledge graph technologies, graph databases, and AI‑powered workflows, with a track record of delivering large-scale initiatives.