Live opening · Posted 11 days ago
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Description supplied by the original job listing.
Requirements:
5 + years of professional software engineering with strong Python (or Java / Kotlin) proficiency.
Hands-on production experience with at least one major graph database: Neo4j, Amazon Neptune, TigerGraph, or comparable.
Demonstrated knowledge of graph query languages like Cypher, SPARQL, or Gremlin at production query complexity.
Direct experience building LLM-powered agents or pipelines using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or Semantic Kernel.
Solid understanding of RAG architectures: chunking strategies, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, and re-ranking.
Familiarity with prompt engineering, few-shot learning, and LLM evaluation techniques.
Experience integrating external data sources via APIs, web scraping (Playwright / Scrapy), or streaming pipelines (Kafka / Kinesis).
Working knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines.
Familiarity with graph export formats - at least one GraphML, RDF/OWL, or JSON-LD.
Experience integrating GNN-derived features into vector stores or RAG pipelines.
Experience
5-9 yrs
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