GenAI Engineer
Core
Design and implement enterprise-scale RAG pipelines and multimodal AI applications using LLMs and vector databases.
Role type
Senior IC GenAI Engineer
Builds
Intelligent applications processing text, images, and documents for enterprise clients
Domain
Generative AI, Retrieval-Augmented Generation (RAG), Vector Search
Deliverable
production ML models
Required skills
Python, RAG solutions, vector databases, embeddings, retrieval strategies, semantic search, prompt engineering, multimodal AI, LLMs, foundation models, AWS AI services, Amazon Bedrock, LangChain, AI evaluation frameworks, AI observability, production deployment
Preferred skills
Agentic AI concepts, LangGraph, multi-agent architectures, MLOps, model deployment pipelines
Technologies
AWS, OpenSearch, LangChain, Pinecone, Weaviate, Milvus, Chroma
Responsibilities
Design and implement enterprise-scale RAG pipelines; Build and optimize semantic search solutions; Develop multimodal AI applications; Create and refine prompts for LLM performance; Develop data ingestion, chunking, embedding, retrieval, and ranking strategies; Evaluate and improve AI solution quality, accuracy, and latency
Seniority
Senior, hands-on IC
