Global AI Data Intelligence & Knowledge Graph Lead

Socket.dev; Santa Clara (CA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Flexible time off

Wellness resources

Company-sponsored team events

Job summary

Everpure in Santa Clara is seeking an AI Data Intelligence & Knowledge Graph Engineer to lead a distributed team of AI/ML, NLP, knowledge graph, and data intelligence professionals in the United States and Prague.

This leader will be responsible for building and scaling the team, setting technical direction, and delivering production-grade capabilities that transform unstructured and structured enterprise data into accurate, contextual, governed, and AI-ready information.

Responsibilities

• Lead and develop a geographically distributed team in the United States and Prague, including hiring, onboarding, coaching, performance management, succession planning, and organizational design.
• Establish a clear team strategy and roadmap for AI data intelligence, knowledge graph capabilities, document intelligence, and AI-ready data workflows.
• Partner with senior leaders in Engineering, Product Management, Architecture, Security, Quality, Customer Success, and Go-to-Market to align priorities and deliver measurable outcomes.
• Guide the design and implementation of production systems that extract entities and relationships, classify and enrich data, build semantic context, and make information useful for AI models, agents, and enterprise applications.
• Lead technical direction across knowledge graph and semantic technologies, including ontology and taxonomy design, entity resolution, graph analytics, graph-based retrieval, and GraphRAG patterns.
• Oversee AI/ML approaches for document intelligence, named entity recognition, information retrieval, classification, embeddings, LLM-assisted workflows, and domain-specific extraction.
• Create a disciplined model and data lifecycle covering dataset generation, annotation, training, evaluation, deployment, monitoring, retraining, and governance.
• Establish quality and reliability standards using measures such as precision, recall, F1 score, accuracy, retrieval effectiveness, false-positive and false-negative rates, drift, and customer-reported outcomes.
• Ensure explainability, traceability, documentation, and responsible-use practices are built into AI systems and workflows from design through production.
• Drive automation across data preparation, training pipelines, regression testing, model evaluation, deployment, observability, and production issue resolution.
• Partner with Product and customer-facing teams to translate enterprise needs into practical AI capabilities for regulated and data-intensive industries, including financial services, healthcare, insurance, retail, government, and technology.
• Build strong operating rhythms across the US and Prague teams, including planning, technical reviews, architecture forums, talent reviews, incident learning, and roadmap communication.
• Recruit and retain exceptional talent in a competitive market, with an emphasis on developing a balanced team across graph engineering, NLP/ML, data science, quality engineering, and applied research.
• Represent the team with executive stakeholders and communicate complex technical concepts clearly to technical and non-technical audiences.
• Promote a culture of intellectual rigor, customer focus, inclusion, accountability, and continuous learning.
• We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

Job description

Everpure in Santa Clara is seeking an AI Data Intelligence & Knowledge Graph Engineer to lead a distributed team of AI/ML, NLP, knowledge graph, and data intelligence professionals in the United States and Prague.

This leader will be responsible for building and scaling the team, setting technical direction, and delivering production-grade capabilities that transform unstructured and structured enterprise data into accurate, contextual, governed, and AI-ready information.