[Job-31910] AI Engineer, Brazil

Role overview A global technology services firm is seeking an AI Engineer to join a delivery team building production Generative AI solutions for a large enterprise client. The role focuses on taking LLM-based use cases from proof of concept through to production, spanning retrieval-augmented generation, document intelligence, and conversational AI, primarily on Azure with some AWS workloads.

Responsibilities - Design, build, and ship LLM-powered features and applications that move beyond PoC into real production use. - Develop and maintain RAG pipelines, conversational agents, and document intelligence workflows using Azure AI services. - Implement solutions that integrate multiple LLM families (OpenAI, Anthropic, Google Gemini, and open-source models) and embedding stores. - Build and maintain CI/CD pipelines and MLOps practices to support reliable model deployment and iteration. - Collaborate with international stakeholders and cross-functional teams to translate business needs into AI solutions.

Requirements - 4+ years in Machine Learning or AI engineering, with at least 2 years hands-on with LLMs and Generative AI. - Proven experience delivering RAG or LLM-based applications beyond PoC. - Strong Python skills and experience with LangChain or comparable frameworks such as LlamaIndex or Semantic Kernel. - Hands-on experience with Azure AI services (Azure OpenAI, Azure AI Search, Azure AI Foundry/AI Studio, Cosmos DB, Blob Storage). - Familiarity with vector databases and embedding models (Azure AI Search, FAISS, or similar). - CI/CD experience with Azure DevOps and/or GitHub Actions, plus MLOps tooling such as MLflow. - Fluent English for daily communication with international stakeholders.

Nice to have - AWS ML services such as SageMaker, Textract, Comprehend, or Bedrock. - Document AI and OCR tools like LayoutLM, Layout-Parser, Tesseract/EasyOCR, or Azure Document Intelligence. - Computer vision, multimodal/vision LLMs, or speech recognition experience. - Fine-tuning open-source models with LoRA/PEFT. - Experience with Kubeflow, Kubernetes, agentic patterns, or containerized model serving.

Benefits and work setup - Health and dental insurance, life insurance, and meal/food allowance. - Childcare assistance and extended paternity leave. - Profit Sharing and Results Participation (PLR). - Well-being platform and partnerships with gyms and wellness professionals. - Continuous learning programs and language learning support. - Position based in Brazil.