AI Engineer, Personalization

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AB InBev

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B2C • eCommerce • Food & Beverage

Somos a maior cervejaria do mundo, unindo pessoas para construir um mundo melhor. Há séculos, a experiência de compartilhar uma cerveja aproxima pessoas e culturas. Mesmo em um mundo hiperconectado e sempre ligado, esse gesto simples é tão significativo hoje quanto foi para gerações passadas.

10.000+ funcionários

👥 B2C

🛍️ Comércio Eletrônico

Descrição

• Design, develop, and deploy multi-agent AI systems for reasoning, planning, and task execution • Implement RAG (Retrieval-Augmented Generation) pipelines using orchestration tools and frameworks (LangChain, LangGraph, Azure AI Foundry) • Optimize model serving for low-latency, high-throughput inference using frameworks like KServe, Triton Inference Server, or Ray Serve • Build observability and evaluation frameworks to monitor agent reasoning, success rates, and failure cases • Collaborate with product managers, data engineers, and security specialists to integrate structured and unstructured data sources into agent workflows • Apply security and alignment techniques (guardrails, prompt injection prevention, red-teaming) to ensure robust behavior • Work in a CI/CD environment (Azure DevOps, GitHub Actions, ArgoCD) for rapid iteration and reliable deployment • Participate in architectural decisions involving distributed systems, GPU usage, caching strategies, and memory management

🎯 Requisitos

• Strong proficiency in Python (for prototyping) • Proficiency in C++ or Go for performance-critical components • Proven experience with LLMs (OpenAI, Anthropic, Llama, Mistral, or similar) • Practical experience with agent orchestration frameworks (LangChain, LangGraph, Semantic Kernel) • Deep understanding of search and retrieval systems and vector databases (Pinecone, Weaviate, FAISS, Milvus) • Experience deploying ML models in Kubernetes/AKS/EKS/GKE environments • Familiarity with ONNX Runtime, TensorRT, or DeepSpeed for inference optimization • Experience with public clouds (Azure, AWS, or GCP) and infrastructure as code (Terraform, CloudFormation, or Bicep) • Understanding of AI security (prompt injection, data leakage, adversarial testing) • Nice to have: multi-agent simulations (AutoGen, CrewAI, OpenAI Swarm) • Nice to have: background in red-teaming and offensive security for AI models • Nice to have: knowledge of graph databases (Neo4j, ArangoDB) for agent memory and reasoning • Nice to have: publications, research contributions, or involvement in open-source projects related to LLM or agent frameworks

🏖️ Benefícios

• Performance based bonus* • Attendance Bonus* • Private pension plan • Meal Allowance • Casual office and dress code • Days off* • Health, dental, and life insurance • Medicines discounts • WellHub partnership • Childcare subsidies • Discounts on Ambev products* • Clube Ben partnership • Scholarship* • School materials assurance • Language and training platforms • Transport allowance • *Rules applied