Senior AI Engineers
Senior AI Engineers
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Job Description
Candidate Requirements
Seniority Level
Senior
Professional Experience
6 years
Technology Stack
Graph Databases: Familiarity with graph databases like Neo4j TypeDB NebulaGraph and ArangoDB indicates experience with storing and managing complex entitybased relationships essential for GraphRAG operations
Knowledge Graph Construction: Skills with knowledge graph frameworks and semantic data modeling are key so look for experience with RDF (Resource Description Framework) SPARQL (for querying RDF) OWL (Web Ontology Language) and tools like Protg. These are crucial for building structured queryable graphs that enhance LLM contextual understanding.
RAG Libraries and LLM Orchestration: Experience with LangChain Haystack or RAGFlowtools that provide RAG pipelines and manage knowledge augmentation for LLMsis valuable. These libraries are often used to implement RAG techniques in LLM applications integrating retrieval systems directly with models
Large Language Model Platforms: Familiarity with LLM frameworks like OpenAIs API Hugging Face Transformers LLamaIndex and Azure Cognitive Services suggests experience with model orchestration and deployment especially for knowledgeaugmented applications.
Python and Graph Query Languages: Proficiency in Python is essential as its the language of choice for building RAG pipelines and integrating with most ML and NLP frameworks. Also knowledge of Cypher (for Neo4j) Gremlin (Apache TinkerPop) and GQL (Graph Query Language) supports direct interaction with graph databases.
Causal Inference Tools: Familiarity with causal reasoning tools like DoWhy EconML or CausalNex is beneficial as these enable causal inference within graph structures supporting the explanatory capabilities that often accompany GraphRAG setups.
Project Responsibilities and Team
Responsibilities on the Project
Experienced Senior AI Engineer with deep expertise in Large Language Models (LLMs) GraphRAG (Graph RetrievalAugmented Generation) and Causal AI is needed to transform the clients current LLMCausal AI prototype into a robust productionready solution. The ideal candidate has strong proficiency in Python a solid grasp of semantics and graph database structures and a passion for building AIdriven products that leverage causal reasoning and knowledge graphs.
Project Team
Will work with a team of 34 other senior engineers
Longterm (612 months)
English: C1
Location:Poland is preferred (Europe is possible)
Ready to Join
We look forward to receiving your application and welcoming you to our team!
Employment Type
Full Time
