Principal Data Engineer, AI Enablement
Core
Design, develop, and maintain scalable AI-ready data solutions, LLM integrations, and graph analytics systems to support machine learning use cases in the pharmaceutical value chain.
Role type
Principal Data Engineer (AI Enablement)
Builds
Scalable data pipelines, LLM-integrated data solutions, graph databases, vector stores, and operationalized ML models.
Domain
Pharmaceutical industry + AI/ML data infrastructure
Deliverable
production ML models
Required skills
MLOps, LLM integration, Data Agents, Agentic Memory, Graph RAG, text mining, unstructured data processing, data pipeline design, ETL/ELT, Python, SQL, distributed data processing (Spark), CI/CD, data governance
Preferred skills
Neo4j, Elasticsearch, AWS
Technologies
Spark, Neo4j, Elasticsearch, AWS, GPT, Claude
Responsibilities
Design and maintain scalable AI-ready data solutions for diverse datasets; Integrate LLMs for data mining, knowledge extraction, and automation; Operationalize machine learning models including deployment and lifecycle management; Capture requirements into expressive data models for graph analytics and GenAI integration; Research and recommend tools for graph databases, vector stores, and LLM integration; Provide technical leadership and act as a subject matter expert on emerging AI technologies.
Seniority
Principal, hands-on IC with strategic advisory
