Top Artificial Intelligence Jobs in Brazil

Serve as technical owner of product quality for AI, automation, and software solutions. Build QMS, design and automate test plans across front-end, backend, AI agents, integrations, and data pipelines. Implement automated test suites, monitoring, drift detection, and intelligent alerts. Validate agent behavior, prompt quality, and large-scale workflow reliability. Partner with engineering and engagement teams to define acceptance criteria, communicate findings, and act as final technical quality gate for client deliverables.

As an AI Data Expert, you will review AI outputs, generate content, and provide structured annotations to improve AI models, ensuring cultural relevance and adherence to guidelines.

As an AI Engineer at SINAI, you'll integrate LLM-powered features, develop AI workflows, and collaborate with cross-functional teams to enhance the platform's capabilities.

The AI Support Engineer provides technical support for AI products, monitors incidents, analyzes agent behavior, and collaborates with teams to improve AI system reliability.

Develop and maintain end-to-end AI-powered financial applications: backend services/APIs, React UIs, real-time systems, and data pipelines. Integrate LLMs and agent architectures, build embedding/vector search and retrieval systems, operationalize AI features, and ensure reliability, observability, and scalability in production.

Develop and optimize a deep-learning compiler stack that converts neural network models (from frameworks) into efficient code for embedded CPUs/DSPs. Use LLVM/MLIR, implement and integrate NN operations, create new optimizations and multiprocessor scheduling, benchmark on DSP/accelerator platforms, validate performance, and collaborate with hardware designers and partners to enable hardware acceleration and standardized APIs.

Intern will learn digital simulation and verification flows, assist engineers running simulations, practice basic automation scripting (Python/TCL), gain exposure to Xcelium/Verisium and Agentic AI, document processes, and participate in mentorship-driven learning.

Design and maintain governed, AI-ready semantic data models and CI/CD pipelines; build data agents and natural-language analytics workflows; partner with analysts, engineers, and stakeholders to translate ambiguous questions into trustworthy, production-grade analytics and AI tools.