, chunking strategies, embedding generation, and vector database integration Build agentic AI systems including single-agent...-tuning, and LLM API integrations 2+ years of experience designing retrieval-augmented generation (RAG) systems and vector...
data models using PostgreSQL and integrate vector databases with relational data sources for contextual responses Define... designing and implementing RAG (Retrieval-Augmented Generation) pipelines, including semantic search, embeddings, and vector...
, PySpark, and cloud platforms (AWS, Azure, or GCP) Apply advanced techniques such as RAG, LangChain, and Vector Databases..., LangChain, and Vector Databases Experience with big data technologies such as Spark, Hadoop, and Kafka Proven solid knowledge...
vector databases and Azure Cognitive Search to ground agents in enterprise knowledge, prior interactions, and operational..., and vector databases Proven solid SQL development skills, including complex joins, window functions, aggregations...
integration, and data engineering. Experience with static analyzers, RAG framework, and relational and vector databases...
, a distilled small language model, or a purpose-built fine-tune. Design and govern AI infrastructure: vector databases, embedding... roles Preferred Qualifications Experience with RAG pipelines, vector search, and knowledge graph integration...
Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone, Weaviate, Chroma, or pgvector Build..., embeddings, vector search, and reranking Working knowledge of at least one agent framework (LangChain, LlamaIndex, LangGraph...
: keyword + semantic search, embeddings, vector databases. - Experience working in production / deploying models (batch...
containerized workloads Integrate with capabilities such as large-scale vector stores for embeddings. Author best practices on the...
), embedding models, vector databases, model evaluation methodologies, and model adaptation techniques. Ability to explain...