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Manager Knowledge Graph Jobs in California (NOW HIRING)

Staff AI/ML Engineer

San Francisco, CA · On-site

$250K - $350K/yr

Expertise in building and managing Knowledge Graphs, including entity extraction, linkage, and ontology design. * Experience integrating Knowledge Graph with AI systems for retrieval, reasoning, and ...

About the Role As an Engineering Manager at Avathon, you will lead the design and delivery of ... Knowledge of graph databases or knowledge graph platforms Interview Process As part of the ...

Staff AI/ML Engineer

San Francisco, CA · On-site +1

$250K - $350K/yr

Expertise in building and managing Knowledge Graphs, including entity extraction, linkage, and ontology design. * Experience integrating Knowledge Graph with AI systems for retrieval, reasoning, and ...

Staff AI/ML Engineer

San Francisco, CA · On-site +1

$250K - $350K/yr

Expertise in building and managing Knowledge Graphs, including entity extraction, linkage, and ontology design. * Experience integrating Knowledge Graph with AI systems for retrieval, reasoning, and ...

Senior Agentic Platform Engineer

Sunnyvale, CA · On-site

$124.30K - $170.70K/yr

... our knowledge graph, supporting the existing team by accelerating technical milestones and ... Experience with unstructured data management and the implementation of vector databases (e.g ...

Senior Agentic Platform Engineer

Cupertino, CA · On-site

$128.90K - $177K/yr

... our knowledge graph, supporting the existing team by accelerating technical milestones and ... You will design cyclic, stateful workflows, implement persistence, and manage Human-in-the-Loop ...

Data Architect, Data Foundry

San Francisco, CA · On-site

$75 - $96.50/hr

... management of disease, and give back to our communities through philanthropy and volunteerism. We ... Knowledge Graph & Specialized Data Systems * Design and implement knowledge graphs (Neo4j, Amazon ...

... with knowledge graph technologies (RDF, property graphs, Neo4j) Experience with data governance practices - data quality, metadata management, or data stewardship Ability to communicate complex ...

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Manager Knowledge Graph information

What is the difference between Manager Knowledge Graph vs Data Analyst?

AspectManager Knowledge GraphData Analyst
Required CredentialsBachelor's degree in Computer Science, Data Science, or related field; knowledge of graph databasesBachelor's degree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentCollaborative teams, often in tech or data-driven companiesOffice setting, analyzing data sets, creating reports
Industry UsageUsed in AI, semantic web, knowledge management projectsUsed across finance, marketing, healthcare for data insights

The Manager Knowledge Graph focuses on designing and managing knowledge graph systems, requiring expertise in graph databases and data modeling. Data Analysts primarily interpret data to generate insights, using statistical tools. While both roles work with data, the Manager Knowledge Graph is more technical and system-oriented, whereas Data Analysts focus on data interpretation and reporting.

What are the most commonly searched types of Knowledge Graph jobs in California? The most popular types of Knowledge Graph jobs in California are:
IT - Technology Architect | CRM | SFDC Sales Cloud

IT - Technology Architect | CRM | SFDC Sales Cloud

Spruce Infotech

Sunnyvale, CA • On-site

$82 - $101.75/hr

Other

This job post has expired today. Applications are no longer accepted.


Job description

Beeline ID+2:28 119095-1
Number of Openings 1
Duration of contract 12 months
No of years' experience 10+ years
Job Title* and Job band Senior Agentic Platform Engineer
Detailed job description - Skill Set*: Senior Agentic Platform Engineer to serve as the lead architect and implementer for our Intelligence Layer. This role is designed for a senior individual contributor who can operate with high autonomy to design, develop, and deploy production-ready solutions that optimize both internal data operations and external-facing intelligence.
You will be responsible for the end-to-end delivery of the connective tissue between our multi-agent architecture and our knowledge graph, supporting the existing team by accelerating technical milestones and hardening the CI/CD processes required for reliable AI deployment
Mandatory Skills *10+ years of Senior Software & Data Engineering experience, with a proven track record of production delivery within a global enterprise environment.
*Advanced Agentic Orchestration (2+ years): Deep, hands-on mastery of LangGraph (StateGraph, Command, and Persistence) and LangChain.
*Multi-LLM Mastery: Expert implementation of frontier models (including Anthropic Claude, OpenAI GPT, and Llama) and the Model Context Protocol (MCP) for standardized tool-calling and context injection across model providers.
*TigerGraph & GSQL Specialist (5+ years): Expert-level proficiency in GSQL development, including writing distributed graph algorithms and optimizing complex sub-queries.
*Knowledge Modeling: Direct experience modeling enterprise ontologies using OWL, SKOS, or RDF and successfully mapping them to Labeled Property Graph (LPG) schemas.
*Analytics Engineering Mastery (5+ years): Expert-level dbt (Core/Cloud) and Snowflake architecture, with specific experience building automated Data Quality (DQ) monitors and trust-score pipelines.
*Development Stack: High proficiency in Python (specifically Asynchronous programming, FastAPI, and Pydantic) and advanced SQL.
*Internal Data Ops Optimization: Demonstrated experience building agents and skills specifically designed to automate Data Governance and Data Operations (e.g., automated glossary curation, schema discovery, and policy enforcement).
Good to Have Skills *Unstructured Data & Vectors: Experience with unstructured data management and the implementation of vector databases (e.g., Pinecone, Weaviate, or Snowflake Cortex Search) within RAG architectures.
*Enterprise Metadata Management: Hands-on experience with DataHub or similar data catalog and metadata management solutions to drive automated discovery.
*Domain Expertise: Familiarity with Sales B2B and B2C data processes and associated tooling (e.g., Salesforce), including experience navigating CRM schemas for agentic tool-calling.
*Governance & Security: Familiarity with data privacy and security frameworks (GDPR, SOC2) as they apply to autonomous agents and Large Language Models.
*Community Engagement: Contributions to open-source agentic frameworks or participation in the development of the Model Context Protocol (MCP) ecosystem.
Vendor Billing range (share in local currency) * XXX/hr (All inclusive)
Work Location (with Zip code of onsite)* 94085
Client Interview / F2F Applicable Yes/Online