Top Artificial Intelligence Jobs in Brazil

Design mobile-first, culturally localized experiences for international member segments using Figma and AI tools. Define AI-native design practices, create high-fidelity prototypes, collaborate with PMs and engineers, run experiments/A-B tests, ensure accessibility and performance, and mentor teammates to deliver scalable, delightful product features.

The role involves onboarding new clients, configuring AI assistants, managing onboarding timelines, and providing client support to ensure successful implementations.

The Lead Software Engineer will build automated frameworks, develop validation strategies, collaborate with R&D, and ensure software quality for AI-driven systems.

The AI Video Editor will develop and produce performance marketing videos, collaborate with various teams, and innovate video production processes while maintaining brand consistency and optimizing video performance based on data.

Develop and maintain MCP tools and the MCP Toolbox for Databases; expand test coverage for agentic coding assistants; refactor and maintain test frameworks; convert technical posts into production-ready sample code and documentation; build real-world data applications (QueryData) to support product R&D and collaborate with cross-functional teams to accelerate agentic AI adoption.

Lead generative AI adoption for enterprise clients: assess AI maturity, design enablement programs, build and optimize prompts and prompt frameworks, develop use cases and PoCs, advise on governance and responsible AI, and train stakeholders.

The Jr. AI Automation Engineer will design, build, and maintain automated workflows for various business processes, utilizing AI tools and Python.

Lead Machine Learning Engineer to execute complex AI research, optimize architectures for production use, and mentor team members, focusing on scalable financial solutions.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

The AI Research Engineer will innovate in model compression for multimodal AI systems, focusing on reducing model size and computational cost while ensuring high performance across edge devices.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

The Data Analytics Specialist will analyze complex data, automate reporting processes, develop models using AI and analytical tools, and create client-ready insights and dashboards.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will optimize model serving and inference architectures, focusing on high-performance, resource-efficient solutions for AI systems across various deployment environments.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

As a Forward Deployed Engineer, you'll build production AI systems, design data infrastructure, and develop ETL/ELT pipelines, collaborating directly with clients to solve complex problems.

As an AI Engineer, you will develop and implement internal automation workflows, integrating various tools and APIs to improve productivity in design and development processes, primarily using LangChain and related frameworks.

As a Senior AI Platform Engineer, you'll maintain and evolve ML infrastructure for scalable AI applications, drive MLOps best practices, and collaborate effectively across teams to standardize engineering excellence.

Lead evaluation and benchmarking of AI-driven genomic interpretation: own gene/disease/variant mapping logic, define accuracy and release criteria, establish regression standards, partner on automated validation, and guide where deterministic logic supplements models.

Design, implement, and run automated benchmarking and validation pipelines for AI-driven genomic interpretation. Expand regression datasets, execute large-scale validation across curated VCFs, surface accuracy regressions, build automated QA for AI releases, and integrate validation into CI/CD with dashboards and documented failure modes.

The role involves building AI-powered backend systems, creating APIs, designing solutions, and enhancing existing systems while ensuring strong problem-solving and communication skills.

The Senior AI Engineer will develop AI-driven solutions using LLMs, focusing on prompt engineering, integration, research, and data utilization for payment systems.

The AI Operations Engineer will build and maintain AI-powered tools for operations, collaborate with stakeholders, and handle multiple daily software releases.

The Senior AI Engineer/Architect will design AI-driven solutions, mentor engineers, evaluate new technologies, and ensure systems align with organizational goals.

The AI Solutions Engineer will build AI-powered prototypes, design workflows, and integrate LLMs into public sector solutions while collaborating with teams to enhance project impact.