Overview:
We are looking for a highly experienced AI Engineer to lead the design and development of advanced Retrieval-Augmented Generation (RAG) applications using the LightRAG framework. This role requires a deep understanding of natural language processing, large language models (LLMs), and scalable system deployment in cloud environments, particularly Microsoft Azure. This position is ideal for candidates who enjoy building high-impact, production-grade AI systems
Tasks
Overview:
We are looking for a highly experienced AI Engineer to lead the design and development of advanced Retrieval-Augmented Generation (RAG) applications using the LightRAG framework. This role requires a deep understanding of natural language processing, large language models (LLMs), and scalable system deployment in cloud environments, particularly Microsoft Azure. This position is ideal for candidates who enjoy building high-impact, production-grade AI systems
Requirements
Location: Remote (Open globally)
Work Hours: EST time zone
Engagement Type: Contract / Full-time (Specify as needed)
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Key Responsibilities:
Architect and implement full RAG pipelines optimized for enterprise-grade use cases.
Integrate and fine-tune state-of-the-art LLMs into the RAG architecture.
Develop and manage scalable vector-based search solutions using ChromaDB, PostgreSQL (Vector extensions), or equivalent.
Build robust and secure AI workflows on Microsoft Azure, leveraging its AI and ML toolsets.
Optimize performance and latency of AI inference and retrieval mechanisms.
Work closely with cross-functional engineering and data teams to ensure seamless system integration.
Participate in code reviews, performance tuning, and system debugging.
Required Skills and Qualifications:
5+ years of experience in AI/ML engineering, including experience in LLM integration.
Demonstrated experience building or leading RAG-based applications using LightRAG or similar frameworks.
Strong programming skills in Python.
Experience working with vector databases and similarity search (ChromaDB, FAISS, Weaviate, PostgreSQL w/ vector).
In-depth knowledge of Azure AI, including deployments, resource management, and security.
Strong understanding of transformer models, embeddings, and prompt optimization.
Excellent problem-solving and communication skills.
