Top Artificial Intelligence Jobs in Brazil

Build responsive, accessible Next.js and React applications for marketing storefronts and clinical platforms. Implement Figma designs, optimize Core Web Vitals, manage client-side state, integrate REST and real-time services, and create AI-powered conversational interfaces while following HIPAA/SOC2 security practices.

Lead end-to-end design and delivery of LLM-backed compliance and risk features: product definition, API design, production deployment, evaluation, human-in-the-loop workflows, observability, and mentoring. Ensure deterministic scaffolding, compliance-safe PII handling, testing, and operational reliability for regulated payment flows.

Use AI-augmented workflows to create marketing campaigns, websites, videos, social content, presentations, and digital assets. Maintain brand quality, prototype and iterate with emerging AI tools, collaborate across teams, and manage multiple projects to improve engagement, conversions, and creative systems.

Perform outbound prospecting (cold calls, email, LinkedIn) to identify and qualify B2B AI SaaS leads, book discovery calls and demos, maintain CRM records, collaborate with marketing and sales, hit monthly KPIs, and stay current on AI/SaaS trends.

Lead and scale demand generation by building signal-driven, automated GTM systems using AI and no-code tools. Own MQL-to-pipeline metrics, optimize CAC, run performance campaigns, integrate CRM and enrichment workflows, collaborate with sales/RevOps to improve conversions and pipeline ROI.

Drive end-to-end high-ticket sales in AI and automation: prospect, conduct discovery calls, nurture leads, manage pipeline in CRM, and close deals. Execute high-volume outbound campaigns using cold calling, email, and LinkedIn while meeting revenue targets and refining outreach with leadership.

Design, develop, and deploy scalable AI/ML solutions using LLMs and generative AI. Build RAG systems, chatbots, automation workflows, and production model pipelines; collaborate with product and engineering teams, monitor and improve model performance, and document systems.

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.

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 develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

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.

Lead discovery and design of enterprise AI solutions, configure AI agents and knowledge structures in PIPE44, guide client onboarding and adoption, measure outcomes, and collaborate with engineers to implement and improve AI operating models and governance.

The GTM Engineer will design and build automated systems for the company's go-to-market engine, focusing on revenue technology and AI capabilities across various teams and markets.

Lead identification, design, deployment, and measurement of AI-powered automation across operations. Build agent and workflow automations, partner with Product/Engineering/Commercial, create dashboards in Metabase, close data gaps, document processes, and evangelize AI tooling to increase operational efficiency.

Design, build, and operate AI-powered backend services and APIs for production LLM features. Ensure reliability, low latency, cost efficiency, observability, and event-driven architectures; review designs and help move experiments to production.

Design and lead architecture for scalable, secure cloud-native SaaS using .NET. Drive API-first, microservices, event-driven patterns; mentor engineers; collaborate with Product, DevOps, and AI teams; champion AI-first tooling and agentic workflows to improve productivity and automation.

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.

Produce high-performing AI-driven paid ads from concept to final cut using AI avatars, voiceovers, b-roll, and motion graphics. Match and iterate on existing ad styles, collaborate with copywriters, optimize for hooks/pacing/CTAs, scale volume, and stay current with AI tools to innovate creative formats.