Data Engineer (SMTS/LMTS) (Knowledge Graph & Artifical Intelligence)

Join Salesforce's Enterprise Knowledge Graph and AI Engineering team as a Data Engineer (SMTS/LMTS). In this role, you will be instrumental in building and scaling the next-generation Enterprise Knowledge Graph platform, which powers AI-driven experiences and intelligent decision-making across the company. You will work closely with cross-functional teams, implement AI-powered engineering tools, and drive technical execution of platform features.

• Design and implement core components of Salesforce's Enterprise Knowledge Graph platform, focusing on performance, data throughput, and system reliability.
• Develop graph data models, write complex graph queries, and construct scalable data pipelines to ingest and map structured and unstructured data to enterprise ontologies.
• Build, integrate, and leverage AI-powered developer tools and engineering automation platforms, driving strategy and productionization.
• Tooling & Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools (e.g., Neo4j, TopQuadrant, Protégé, RDF/OWL, SPARQL, SHACL, property graphs) and semantic reasoning frameworks
• Delivery: Track record of owning and successfully delivering complex features in an agile, production-scale environment
• SMTS
• Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows (e.g., Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks)
• Graph & Ontology Fundamentals: Solid experience working with graph databases and semantic web concepts (e.g., Neo4j, RDF/OWL, SPARQL, property graphs) and mapping data to structured taxonomies
• LMTS
• Leadership: Demonstrated experience leading feature teams, guiding technical execution, and mentoring mid-to-senior level engineers
• Distributed Systems & Cloud: Proven experience building applications on cloud-native systems (AWS, GCP, or Azure) utilizing microservices, REST/gRPC APIs, and event-driven data streaming (e.g., Kafka)
• Core Programming: Expert-level coding skills in backend ecosystems, with strong fluency in Python and standard object-oriented/functional programming languages
• Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routers using Python (leveraging native embeddings, LangChain, semantic-router, or specialized mathematical logic like cosine similarity) to decouple intent handling from expensive LLM calls
• Backend & Cloud: Strong experience with cloud-native system designs (AWS, GCP, or Azure), distributed systems, microservices, and high-throughput event-driven systems
• Ontology & Graph Expertise: Solid, hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems
• Education: A related technical degree required
• Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms
• Semantic Routing & AI: Hands-on experience developing and deploying custom semantic routers using Python (leveraging native embeddings, LangChain, or mathematical logic like cosine similarity) alongside RAG architectures, vector search platforms, and AI workflows
• AI & Retrieval: Proven experience implementing graph-powered AI solutions, vector search platforms, Retrieval-Augmented Generation (RAG) architectures, and orchestrating agentic workflows
• Experience: 8+ years of hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms
• Developer Automation: Experience deploying and integrating AI-assisted engineering tools or automation workflows using ecosystems like Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks
• Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field
• Experience building integrations with data platform environments like Salesforce Data Cloud or enterprise CRM metadata architectures
• Familiarity with ontology validation frameworks (e.g., SHACL) and data quality governance
• Experience optimizing low-latency applications and heavy-throughput vector search lookups
• Passion for engineering automation and driving personal/team velocity via advanced AI development tools
• Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field with a focus on Semantic Web or Knowledge Representation
• Direct experience integrating platforms with Salesforce Data Cloud, CRM platforms, or metadata-driven system designs
• Experience with semantic routing at enterprise scale, high-throughput enterprise search systems, and graph-powered recommendation engines
• Deep familiarity with advanced ontology governance, federated knowledge management, and data contract alignment
• Proven track record of optimizing engineering team velocity through the tailored implementation of AI developer tooling