DE&A - AIML - Data Science - Machine Learning
oraclecloud
Job Description
- Design, build, and maintain Knowledge Graphs in Neo4j, defining node labels, relationship types, and ontologies for complex domains.
- Develop GraphRAG pipelines, combining graph traversal with LLM-based generation for intelligent question-answering and search.
- Write optimized Cypher queries for data retrieval, pattern matching, and graph analytics.
- Build and manage data ingestion pipelines from structured and unstructured sources into Neo4j using Python.
- Integrate vector databases alongside Neo4j for hybrid semantic + graph search.
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GenAI & LLMs
- Experience with LLM frameworks — LangChain, LlamaIndex, or similar — for building RAG applications.
- Understanding of embedding models, vector search, and semantic similarity.
- Prompt engineering and chaining experience for structured outputs.
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Programming & Data Engineering
- Proficient in Python — data pipelines, API integrations, and scripting.
- Experience with data pipeline tools (Airflow, Prefect, or similar).
- Comfortable with REST APIs and working with JSON/CSV/structured datasets.
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Good to Have
- Cloud experience — AWS (Bedrock, SageMaker) or Azure (OpenAI Service).
- Knowledge of graph analytics — Neo4j GDS library (PageRank, community detection, pathfinding).
- Exposure to streaming platforms like Kafka or Spark for real-time graph ingestion.
- Familiarity with GraphQL or Spring Data Neo4j for application integration.
- Experience with visualization tools — Neo4j Bloom, Gephi, or Linkurious.