Graph Engineer

CORTEX; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Cortex is building intelligent knowledge systems for biopharma, aiming to accelerate data interpretation and laboratory automation. We are hiring a senior engineer to lead the development and optimisation of our core knowledge graph, writing production code and guiding architectural decisions with the founders and engineering team.

You will shape graph schemas, entity linking, and query performance, working across science, ML, and backend groups to deliver robust, scalable graph solutions for

Qualifications

• PhD in Computer Science or related field with strong research background is required.
• At least 2 years of industry experience building knowledge graphs or closely related data systems.
• Hands-on experience with graph modeling, data integration, and query development.
• Strong ontology and schema design skills with semantic constraint definitions.
• Experience with one graph platform (Neo4j, Neptune, GraphDB) and query languages (Cypher, SPARQL, or Gremlin).

Responsibilities

• Lead the development and optimisation of core knowledge graph architecture.
• Design schemas, ontologies, and relationship constraints for scientific data.
• Improve entity linking, deduplication, and data quality across sources.
• Write production code for graph components and guide backend integration.

Skills

Knowledge graphs

Ontology design

Graph databases

Graph querying

Performance optimization

Production code

Education

PhD in Computer Science or related field

Tools

Neo4j

Amazon Neptune

GraphDB

Cypher

SPARQL

Gremlin

Job description

Cortex is building intelligent knowledge systems for biopharma, helping scientific teams interpret complex experimental data and advance laboratory automation. We're a venture backed startup in SF and work towards the end of making science move at the speed of the scientific imagination.

We are hiring a senior engineer to lead the development and optimisation of our core knowledge graph. You will also write production code and take substantial responsibility for architecture, performance, and reliability, working closely with the founders and engineering team.

Responsibilities

• Knowledge graph architecture: Design and evolve graph schemas, ontology mappings, and relationship constraints that represent scientific data accurately. Work with scientific and ML teams to ensure the graph supports the product’s reasoning and retrieval requirements.
• Graph construction and quality: Improve entity linking, deduplication, and relationship validation across data sources. Establish evaluations for graph completeness, consistency, and correctness, and use the results to identify and resolve structural and semantic issues.
• Graph querying and optimization: Design and optimize graph queries, traversal strategies, and indexes for real application workloads. Diagnose performance bottlenecks and demonstrate improvements in query latency, scalability, and resource efficiency.
• Implementation and technical direction: Write production code for core graph components, including query interfaces and validation tools. Lead graph architecture decisions and collaborate with backend engineers to integrate these components reliably into the product.

Required qualifications

• Education and experience: You hold a PhD in Computer Science or a related technical field and have at least 2 years of relevant industry experience, or you have 6+ years of industry experience building knowledge graphs, graph databases, or closely related data systems. Relevant research backgrounds include knowledge representation, databases, and graph algorithms.
• Production knowledge graphs: You have at least 2 years of hands-on experience designing, building, and maintaining knowledge graphs, including a system deployed for real users. Your work has included graph modeling, data integration, and query development.
• Knowledge representation: You have strong skills in ontology and schema design, entity linking, and relationship modeling. You understand how to define semantic constraints and evaluate graph consistency and correctness.
• Graph databases and query languages: You have substantial experience with at least one graph platform, such as Neo4j, Amazon Neptune, or GraphDB. You are proficient in SQL and at least one graph query language, such as Cypher, SPARQL, or Gremlin.
• Graph algorithms and optimization: You understand graph traversal, indexing, and computational complexity. You have practical experience profiling graph workloads and improving query performance through changes to queries, indexes, or data models.

Preferred Qualifications:

• Technical ownership: You have independently led a substantial graph or database project, made architectural decisions, and worked with other engineers to deliver and maintain the implementation.