Principal Knowledge Engineer

About the role

The Roleforce is seeking a Principal Member of Technical Staff (PMTS) to lead the technical vision and architecture for Salesforce's Enterprise Knowledge Graph platform. This role will define and drive the long-term strategy for Knowledge Graph platforms, semantic technologies, ontology-driven systems, graph data engineering, and AI-powered developer productivity solutions.

Responsibilities

• Define and drive the long-term technical vision, architecture, and roadmap for Salesforce's Enterprise Knowledge Graph platform.
• Lead architecture and design for knowledge graph ecosystems, including graph data models, ontologies, semantic layers, entity resolution frameworks, graph APIs, vector search capabilities, and retrieval architectures supporting AI and agentic use cases.
• Establish enterprise standards, governance models, engineering patterns, and best practices for Knowledge Graph development, deployment, and lifecycle management.
• Define strategies for integrating structured, unstructured, and third-party data sources into graph-based platforms using scalable data engineering patterns.
• Partner with Architecture, Product, AI Platform, and Data Engineering organizations to align platform investments with enterprise priorities and future AI initiatives.
• Drive technical direction for semantic routing, graph-powered retrieval, enterprise search, agent orchestration, and federated knowledge access patterns.
• Lead evaluation, selection, and adoption of graph technologies, semantic platforms, vector databases, and AI infrastructure required to support enterprise-scale workloads.
• Define and drive the strategy for AI-powered developer tooling, engineering automation, and productivity platforms that leverage technologies such as Claude, Cursor, Windsurf, AI Agents, MCP frameworks, and related AI ecosystems.
• Lead teams in productionizing AI-enabled engineering solutions, ensuring scalability, security, governance, reliability, and measurable productivity improvements.
• Provide technical leadership and architectural guidance across PMTS, LMTS, SMTS, and contractor teams while driving alignment across multiple organizations.
• Serve as the primary technical authority for complex architectural decisions, platform investments, and long-term engineering strategy.
• Foster innovation and continuous improvement while establishing a culture of engineering excellence, technical rigor, and operational maturity.

Requirements

• 12+ years of experience in software engineering, data engineering, distributed systems, enterprise data platforms, or related technical domains.
• A related technical degree required.
• Proven experience defining and delivering enterprise-scale Knowledge Graph platforms supporting AI, semantic search, data integration, and agentic applications.
• Deep expertise in Knowledge Graph technologies, ontology engineering, semantic modeling, linked data, graph databases, and enterprise metadata management.
• Strong hands-on experience with graph technologies such as Neo4j, TopQuadrant, RDF/OWL, SPARQL, property graph models, semantic reasoning frameworks, or similar technologies.
• Proven experience leading the architecture and implementation of graph-powered AI solutions, semantic retrieval systems, vector search platforms, RAG architectures, and agentic workflows.
• Demonstrated success in building, scaling, and productionizing AI-powered developer tools, engineering platforms, or automation solutions using technologies such as Claude, Cursor, Windsurf, GitHub Copilot, AI agents, MCP frameworks, or similar ecosystems.
• Strong experience designing enterprise data engineering architectures, including large-scale ingestion, transformation, orchestration, metadata management, and data governance frameworks.
• Experience with cloud-native architectures and platforms including AWS, GCP, or Azure.
• Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.
• Demonstrated ability to influence senior technical leaders, executives, architects, and cross-functional stakeholders.
• Proven track record of defining technical strategy and driving execution across multiple teams and organizations.
• Excellent communication, leadership, and stakeholder management skills.

Qualifications

• Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, Information Systems, or a related field.
• Experience building enterprise Knowledge Graph platforms supporting large-scale AI and agentic ecosystems.
• Experience with Salesforce Data Cloud, CRM platforms, metadata-driven architectures, or enterprise data platforms.
• Experience with semantic routing, enterprise search, graph-powered recommendation systems, and intelligent retrieval architectures.
• Experience with vector databases, Retrieval-Augmented Generation (RAG), AI agents, MCP frameworks, and emerging AI infrastructure technologies.
• Experience leading enterprise-wide platform initiatives spanning multiple organizations and business domains.
• Strong understanding of ontology governance, federated knowledge management, and enterprise semantic architecture.
• Demonstrated track record of driving measurable improvements in engineering productivity through AI-powered tooling and automation.

Skills

• Knowledge Graph technologies, ontology engineering, semantic modeling, linked data, graph databases, and enterprise metadata management.
• Hands-on experience with graph technologies such as Neo4j, TopQuadrant, RDF/OWL, SPARQL, property graph models, semantic reasoning frameworks, or similar technologies.
• Proven experience leading the architecture and implementation of graph-powered AI solutions, semantic retrieval systems, vector search platforms, RAG architectures, and agentic workflows.
• Strong experience designing enterprise data engineering architectures, including large-scale ingestion, transformation, orchestration, metadata management, and data governance frameworks.
• Experience with cloud-native architectures and platforms including AWS, GCP, or Azure.
• Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.
• Ability to influence senior technical leaders, executives, architects, and cross-functional stakeholders.
• Excellent communication, leadership, and stakeholder management skills.

Benefits

At Salesforce, we offer a comprehensive benefits package to support your well-being and financial security. This includes:

• Time off programs
• Medical, dental, vision, mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program

For more details, visit Salesforce Benefits.

Pay

The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually.

Schedule

This role is full-time.