Senior GenAI RAG Engineer

Job not on LinkedIn

🕒 August 4

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 29%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Compass

WebsiteLinkedInAll Job Openings

10,000+ employees

🏠 Real Estate

📱 Media

Real Estate • Media

Compass is a real-estate-focused content and services site that provides detailed market analysis, buying/selling/renting guides, mortgage and financing information, and home improvement and renovation advice. The site offers resources for homebuyers, sellers, renters, agents, and real estate investors — including articles on appraisals, affordable housing, investment strategies, staging and property maintenance. Compass aims to help users make informed decisions across the housing lifecycle through timely market updates and practical how-to content.

📋 Description

• Develop and evolve AI Agents for production environments • Design and implement RAG (Retrieval-Augmented Generation) architectures • Build ingestion, processing, indexing and retrieval data pipelines • Integrate LLMs with systems, APIs and enterprise platforms • Optimize inference workflows, ensuring performance, scalability and reliability • Implement best practices for security, governance and solution quality • Collaborate on defining the technical architecture and advancing the AI platform • Monitor, document and drive continuous improvements in the solutions

🎯 Requirements

• Experience with Generative AI, LLMs and developing AI Agents • Experience building RAG architectures • Proficiency in Python • Experience with LangChain, LangGraph, LlamaIndex or similar frameworks • Knowledge of vector databases and techniques for embeddings, chunking and semantic search • Experience with REST APIs, Git and Docker • Knowledge of cloud services (AWS, Azure or GCP) • Experience with CI/CD and deploying applications to production • Knowledge of security and governance for AI solutions • Nice-to-have: experience with Azure OpenAI, Amazon Bedrock or Vertex AI • Nice-to-have: knowledge of LLMOps/MLOps and observability • Nice-to-have: familiarity with Kubernetes, GraphRAG, MCP and multi-agent systems • Nice-to-have: technical English