Top Artificial Intelligence Jobs in Brazil

The AI Specialist responds to customer inquiries, troubleshoots tech issues related to AI, and collaborates with teams for client satisfaction.

Build and maintain end-to-end data pipelines, models, data marts, and semantic layers for marketing, client, BI, product, and AI consumers. Integrate fragmented advertising and customer data across multiple platforms and tenants, manage dbt projects, ensure data quality, optimize performance, and support client-specific modeling. Use AI-assisted development workflows, collaborate cross-functionally, and deliver reliable, AI-ready data products.

Build, test, tune, and scale SIEM and data-lake detection rules using threat intelligence, MITRE ATT&CK, and detection-as-code workflows. Investigate false positives, improve alert fidelity, collaborate with SOC, threat hunting, threat intelligence, and data engineering teams, and develop coverage for emerging threats. Use AI agents, LLM-assisted tooling, MCP, and machine-learning techniques to accelerate rule development, validation, telemetry analysis, and anomaly detection.

Build production LLM agents, multi-step workflows, MCP servers, evaluation and observability systems, and document-extraction pipelines. Architect AI-ready semantic data layers over Snowflake and dbt, develop Python ingestion and Airflow workloads, and implement retrieval, embeddings, governance, security, and reliable agent operations. Lead technical design, mentor peers, and advise clients in an embedded consulting engagement.

Lead the engineering of AI initiatives, architect stacks, prompt engineer LLMs, and mentor engineers. Work closely with cross-functional teams to deliver products from concept to production.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

Transform Cursor into an engineering multiplier by optimizing AI-assisted development workflows, auditing AI-generated code, and mentoring developers on AI use in their workflow.

Convert raw workshops, interviews and long-form video into high-volume micro-content, sizzles, courses and high-converting landing/funnel pages using AI tools. Manage asset libraries, QA, reporting, CRM integrations and rapid revisions to meet SLAs.

Senior technical leader providing high-level AI strategy, architecture direction, and long-term systems design. Delivers strategic artifacts (architecture reviews, AI integration strategies, roadmaps), advises executives, collaborates with product and engineering teams, and mentors technical leaders to improve scalability, resilience, and governance across platforms.

The Principal AI Engineer will lead the design and deployment of AI systems, drive AI strategies, and mentor teams. They require extensive experience in building AI solutions and integrating ML with applications, alongside strong leadership skills.

Lead creative excellence at Superside, leveraging AI tools to shape branding and ads while mentoring a global creative team.

The Applied AI Researcher will design experiments, build pipelines, and advance domain-specific AI models, focusing on training, evaluation, and knowledge representation.

Lead research on domain-specific AI models, defining strategies for model lifecycle and evaluation, while mentoring senior researchers and causing impactful outcomes in various sectors.

The Senior Applied AI Researcher will lead end-to-end research projects on agentic AI, focusing on model training, multimodal systems, and mentoring junior researchers while driving rapid prototype deployment to production.

As a Data Scientist, you'll work on client projects and research initiatives, utilizing machine learning and data-driven solutions to solve real-world problems and contribute to AI alignment research.

Design and build AI-powered applications, create scalable AI pipelines, and integrate AI models into applications while collaborating with teams to deliver products.

The AI Lead designs and implements AI solutions for clients, driving client relationships, monitoring success metrics, and collaborating with product teams to enhance customer journeys.

Design, build, and operationalize AI agentic solutions across the software lifecycle. Own backend responsibilities, contribute to frontend, define technical requirements, deliver maintainable code, collaborate with clients, and stay current with AI, LLM orchestration, and evaluation practices.

The LATAM Commercial Productivity & AI Specialist will identify and implement AI solutions to enhance business efficiency and decision-making across the LATAM region.

Design, build, and deploy bespoke AI/LLM-driven agent solutions on the Salesforce platform. Own end-to-end technical delivery: data modeling, integration, model orchestration, debugging, prototyping, and client-facing implementation to ensure scalable, secure, and high-impact deployments.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

Designs and delivers production-grade GenAI and agentic AI solutions for enterprise clients. Leads discovery, solution architecture, rapid prototyping, technical presales, evaluation, integration, and MVP or first-production delivery. Works with LLMs, enterprise data, workflows, orchestration, vector databases, cloud AI services, and tool-calling systems. Translates ambiguous business problems into validated solutions while addressing cost, security, compliance, observability, responsible AI, adoption, and production readiness.

Design, build, and scale full-stack applications with a backend focus. Build APIs, integrations, and user-facing frontends. Contribute to AI-powered features, system architecture, performance optimization, testing, and code reviews. Collaborate with product and client teams, own features end-to-end, and deliver measurable business outcomes in a remote environment.

Lead design and evolution of scalable, secure cloud-native SaaS platforms using C#/.NET. Define architecture standards, drive microservices/DDD/CQRS/event-driven designs, mentor engineers, improve performance, security, observability, and integrate AI-assisted development tools to increase productivity across teams.

Lead architecture and technical standards for cloud-native, AI-first SaaS products using .NET and microservices. Define DDD/CQRS/event-driven designs, mentor engineers, drive performance, security, observability, and integrate AI-assisted development workflows.