Knowledge Graph Engineer

We are seeking a Knowledge Graph Engineer with hands-on experience in data engineering and graph technologies to design, build, and maintain scalable knowledge graph solutions. You will translate ontologies and semantic models into production systems, develop pipelines that connect enterprise data to graph platforms, and build queries that support downstream analytics and intelligent applications.

This role is ideal for someone who combines strong software engineering fundamentals with an understanding of graph modeling and semantic data. You will own solutions from architecture and technology selection through implementation, testing, and performance optimization, working closely with data engineers, AI teams, and stakeholders to turn business requirements into reliable systems.

What you will do

• Maintain and extend our knowledge graph, including its schema, ingestion pipelines and query layer (Neo4j, Cypher, Apache Jena Fuseki, BigQuery on Google Cloud).
• Build and run validation and data-governance pipelines to maintain data quality, consistency, and performance. This covers schema and constraint checks, identifier reconciliation, provenance and versioning.
• Maintain our ontologies and semantic models with the biology and data science teams, and develop the mapping tool scientists use to annotate new terms and analyses. This includes the validation that keeps their mappings consistent with the graph.
• Integrate knowledge graph solutions with cloud platforms and enterprise data ecosystems, including Google Cloud and BigQuery.
• Collaborate with data engineers, data science, AI and biology teams to make graph data accessible and useful for downstream applications.
• Write clean, testable, production-grade code and apply engineering best practices throughout development and delivery.

What you bring

Basic qualifications

• Bachelor's degree or higher in computer science, data engineering, AI or a related field, with 3+ years of industry experience in data engineering.
• Experience working with biological or biomedical data, such as genomics, proteomics, clinical or phenotype data, and familiarity with standard biomedical ontologies and identifiers (e.g. UniProt, Gene Ontology, EFO, MONDO).

Technical qualifications

• Hands-on experience with graph databases such as Neo4j, Stardog or GraphDB, including writing and optimizing queries in Cypher or SPARQL.
• Working knowledge of semantic modelling concepts and standards such as RDF and OWL, and the ability to turn an ontology into a working schema.
• Experience designing and building APIs (e.g. REST or GraphQL, using frameworks such as FastAPI) that give applications and users access to graph data.
• Experience building data-quality or validation frameworks.
• Familiarity with Google Cloud and BigQuery.
• Strong Python and working knowledge of JavaScript for building data pipelines, graph integrations, and production applications.
• Strong software engineering practices, including data modeling, system design, testing, documentation and version control.
• (Preferred) Experience with LLM or agent systems
• (Preferred) Experience with Open Targets and other drug-discovery knowledge bases.

Collaboration and ownership

• Strong problem-solving skills and sound technical judgment when requirements are still evolving or design priorities compete.
• Ability to take ownership of a solution from initial design through implementation and ongoing maintenance.
• Clear written and verbal communication, including the ability to explain architecture decisions and technical trade-offs to clients and stakeholders.
• Ability to work effectively across data engineering, biologists and AI teams.

Our company

BioAge is a clinical-stage biopharmaceutical company developing therapeutic product candidates for metabolic diseases by targeting the biology of human aging. The Company's lead product candidate, BGE-102, is a potent, orally available, brain-penetrant small-molecule NLRP3 inhibitor being developed for cardiovascular risk and retinal diseases including diabetic macular edema. BGE-102 has completed a Phase 1 SAD/MAD trial demonstrating a well-tolerated profile and potential best-in-class reductions in hsCRP and other inflammatory biomarkers in participants with obesity and elevated inflammation. Phase 2 cardiovascular risk proof-of-concept data are anticipated in H2 2026, and Phase 1b/2a diabetic macular edema proof-of-concept data are anticipated in mid 2027. The Company is also developing long-acting injectable and oral small molecule APJ agonists for obesity. BioAge's additional preclinical programs, which leverage insights from the Company's proprietary discovery platform built on human longevity data, address key pathways involved in metabolic aging. BioAge has been listed on Nasdaq (BIOA) since 2024. For additional information about BioAge, visit the company's website at https://bioagelabs.com.

Our workplace

BioAge offers competitive salary, a comprehensive compensation package, and generous paid time off in addition to company-observed holidays. We provide comprehensive health and wellness benefits (medical, dental, and vision insurance) and a 401(k) retirement savings plan with matching employer contributions, and we support families through childcare and fertility benefits. We also pride ourselves in giving employees many opportunities for career development, including a generous annual budget for continued learning and a dedication to training and skill development. Many positions (including this one) are remote, allowing our team members to work from anywhere. The salary for this role is expected to be approximately $140,000 - $175,000, depending on experience. We are open to the concept that different experience levels add value to the team in different ways, and therefore will consider a variety of experience and offer commensurate pay.