RAG Architect

Há 3 dias

Buenos Aires, Brasil Perform Tempo inteiro

Join to apply for the RAG Architect role at Perform

We are seeking a Senior AI Engineer to lead the design and implementation of an end-to-end Retrieval-Augmented Generation (RAG) architecture. This role will drive the ingestion of GitHub repositories, Confluence pages, Qtest artifacts, PRDs, and script libraries to power autoscripting, onboarding search, and long-term knowledge reuse. As a technical leader, you will set the strategic direction, select cutting-edge models, and mentor AI and Automation Agent Engineers to deliver a scalable, secure, and innovative platform.

Key Responsibilities
  • Architect ingestion and retrieval layers, selecting loaders, chunking strategies (AST-aware for Java), embeddings (e.g., BGE-Code, mxbai), vector stores (e.g., Chroma), cross-encoder rerankers, and LangChain router chains.
  • Design CI orchestrations, including daily Jenkins jobs for delta detection, image captioning (e.g., Qwen2-VL, LLaVA), cost/latency guardrails, and rollback strategies.
  • Establish model and prompt governance, including prompt templates, few-shot libraries, safety filters, and evaluation rubrics (faithfulness, coverage, compile success).
  • Lead architecture for a UI onboarding tool, deciding on hosting (FastAPI + React or Streamlit MVP), SSO/auth flows, token streaming, and feedback mechanisms for continuous learning.
  • Oversee data security and compliance, embedding privacy policies, source citations, audit logs, and ensuring Confluence/Qtest credentials are managed in Secrets Manager.
  • Provide technical leadership by reviewing PRs, setting code quality standards, and conducting architecture workshops for AI and Automation Agent Engineers.
Must-Have Qualifications
  • 6–8 years of experience building data or ML platforms, with at least 2 years deploying LLM/RAG systems in production.
  • Deep expertise in LangChain, ChromaDB, Qdrant, or pgvector, and cross-encoder rerankers.
  • Strong proficiency in Python (FastAPI or Flask) and ability to analyze Java codebases for chunking boundaries.
  • Proven experience designing CI/CD pipelines (Jenkins, GitHub Actions) with delta builds and artifact promotion.
  • Hands-on experience managing OpenAI/Anthropic API keys or self-hosting large models.
  • Demonstrated expertise in security and compliance, including PII protection, role-based access, and secret rotation.

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