Senior LLM Engineer (RAG & AWS Bedrock)
Quick Summary
Join Our Team Oowlish, one of Latin America's rapidly expanding software development companies, is seeking experienced technology professionals to enhance our diverse and vibrant team.
About the Role
~2 min readWe are looking for an experienced Senior LLM Engineer to build an AI-powered data intelligence platform that enables users to interact with multiple enterprise data sources through natural language.
This role focuses on designing and implementing Retrieval-Augmented Generation (RAG) solutions, semantic search, and conversational AI experiences powered by AWS Bedrock. You will build scalable AI pipelines capable of retrieving, processing, and synthesizing information from multiple structured and unstructured data sources into an intuitive chatbot experience.
The ideal candidate has strong experience building Generative AI applications, designing RAG architectures, and working with vector search, embeddings, and cloud-native AI services.
- Embeddings
- Vector Search
- Semantic Search
- Experience building AI-powered chatbot applications.
- Experience designing multi-source data ingestion pipelines.
- Experience working with S3 Data Lakes.
- Strong Prompt Engineering experience.
- Experience integrating multiple enterprise data sources.
- Strong understanding of Large Language Models (LLMs).
- Experience designing scalable AI architectures.
- LangChain
- LlamaIndex
- Pinecone
- Weaviate
- OpenSearch Vector
- ChromaDB
- FAISS
- Experience building conversational AI applications.
- Experience with enterprise knowledge management systems.
- Experience with API Gateway.
- Experience with EventBridge or SQS.
- Experience with Infrastructure as Code.
- Experience optimizing LLM performance and retrieval quality.
- Experience with connected TV (CTV), AdTech, or advertising analytics platforms.
Location & Eligibility
Listing Details
- Posted
- June 26, 2026
- First seen
- June 26, 2026
- Last seen
- June 27, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- June 26, 2026
Signal breakdown
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