Knowledge Engineering Semantic Expert (AI)

Location: Hybrid, United States; listed offices include Chicago, Milwaukee, Dallas, Columbus, Kirkland, Cincinnati, New York, Cleveland, Oklahoma City, Austin, Albany, St. Pete, Hartford, Pittsburgh, St. Louis, Miami, Sacramento, Raleigh, Minneapolis, Mountain View, Scottsdale, San Francisco, Morristown, Denver, Boston, Philadelphia, Des Moines, Overland Park, Los Angeles, Charlotte, Walnut Creek, Carmel, Seattle, Houston, Arlington, Atlanta, Orlando, Redmond, Bentonville, Beaverton, Nashville, Detroit, and San Diego. Travel may range from 0% to 100% based on business and client requirements.

Salary: $87,400–$253,800 annual salary range for Illinois; compensation varies by office, role, skills, and experience.

Company

hirify.global is a global professional services company focused on digital transformation, cloud, data, AI, cybersecurity, and industry solutions.

What you will do

• Architect and implement production knowledge graph solutions using RDF triple stores and property graph technologies.
• Translate semantic architectures, ontologies, and enterprise data models into scalable technical implementations.
• Build Python and PySpark ingestion and transformation pipelines for relational, document, streaming, and unstructured data.
• Implement identity resolution, entity disambiguation, entity linking, and link prediction for canonical enterprise graph records.
• Integrate graph databases with data lakes, lakehouses, analytics platforms, APIs, vector stores, and AI applications.
• Develop GraphRAG systems, high-throughput REST, GraphQL, and gRPC services, while mentoring engineers and improving production reliability.

Requirements

• At least 5 years of hands-on Big Data, data engineering, or analytics engineering experience, including scalable ETL/ELT pipelines for batch and/or streaming workloads.
• At least 2 years of Python experience with relevant libraries and frameworks such as PySpark, RDFLib, NetworkX, and FastAPI.
• At least 2 years of experience with graph query and data languages including SPARQL, Cypher, RDF, and/or SQL.
• At least 2 years of experience with knowledge graph and graph database technologies such as Neo4j, Stardog, GraphDB, and/or Amazon Neptune.
• Hands-on production engineering experience covering high availability, low latency, scalability, observability, performance optimization, and resiliency.
• Applicants for employment in the United States must already have work authorization that does not now or in the future require visa sponsorship.

Nice to have

• Databricks or comparable modern data platforms, including Spark SQL, Delta Lake, Snowflake, Unity Catalog, and enterprise lakehouse architectures.
• Lakehouse-to-graph ingestion pipelines and large-scale semantic data transformation.
• GraphRAG, RAG, vector search, and hybrid vector-graph architectures for generative AI applications.
• SHACL, graph schema validation, ontology versioning, and semantic data-quality frameworks.
• Production RDF and/or property graph architectures, regulatory or compliance-driven modeling, and graph-based ML alongside symbolic modeling.

Culture & Benefits

• Full-time employment in a hybrid workplace with travel varying from 0% to 100% according to business and client needs.
• Medical, dental, vision, life, and long-term disability coverage.
• 401(k) plan, bonus opportunities, paid holidays, and paid time off.
• Inclusive workplace with equal employment opportunity and reasonable accommodation support.