AI Search & Knowledge Graph Engineer (RAG / LLM Systems)

Key Responsibilities

• Develop and enhance AI-powered semantic search capabilities, including natural-language query understanding and contextual response generation.
• Design and implement retrieval-augmented generation pipelines (RAG/GraphRAG), including vector embeddings and semantic indexing.
• Build and maintain graph database models and queries using Neo4j (Cypher) or equivalent technologies.
• Integrate LLM services (e.g., Azure OpenAI) via secure and scalable APIs.
• Develop backend services using Node.js, TypeScript, or similar frameworks.
• Support SQL-based reporting, analytics, and data extraction across SQL Server, MySQL, or Oracle.
• Design and maintain ETL workflows for data ingestion, normalization, and enrichment across multiple content sources.
• Contribute to UI/UX improvements for search and knowledge discovery interfaces.
• Collaborate with internal teams to define system architecture, workflows, and integration patterns.
• Produce technical documentation, design specifications, and support knowledge transfer activities.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• Experience building AI-powered search, semantic search, or knowledge discovery systems.
• Strong understanding of vector embeddings, RAG, GraphRAG, or similar retrieval-augmented frameworks.
• Hands-on experience with graph databases (Neo4j/Cypher or equivalent).
• Proficiency in Node.js, TypeScript, or similar backend technologies.
• Strong experience with SQL databases and data-driven reporting/analytics.
• Experience integrating LLM APIs (e.g., Azure OpenAI or similar platforms).
• Strong understanding of REST APIs and modern software development practices.

Preferred Qualifications

• Experience with GraphQL and Apollo.
• Background in ETL pipeline development and data engineering.
• Front-end development experience (HTML, CSS, JavaScript frameworks).
• Experience working with enterprise knowledge systems, search platforms, or content management systems.
• Strong documentation, communication, and stakeholder collaboration skills.
• Ability to work independently with minimal supervision and periodic check-ins.

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