Top Artificial Intelligence Jobs in Brazil

Build and scale primarily backend-focused full-stack applications for Chiri and its clients. Develop APIs, integrations, frontend experiences, AI-powered solutions, automations, and internal products using Python and TypeScript. Translate business requirements into scalable systems, participate in architecture and code reviews, optimize performance and reliability, and own features through deployment and support while collaborating with engineers, product stakeholders, and clients.

Define and govern enterprise data architecture across batch, streaming, lakehouse, warehouse, and operational workloads. Lead data-mesh adoption, data products, semantic models, governance, quality, lineage, security, and observability. Architect real-time event-processing platforms using Kafka, Kinesis, Flink, Spark, and Databricks, while guiding cloud data platforms and MLOps capabilities across AWS and GCP. Advise architects and domain teams, lead RFCs and design reviews, resolve critical architectural issues, and mentor data and engineering professionals.

Build and deploy full-stack AI applications, including React interfaces, Python or Node services, agentic systems, RAG pipelines, data pipelines, evaluations, and cloud infrastructure. The role requires production engineering practices, AI platform expertise, client communication, pre-sales support, and mentoring junior engineers.

Build and deploy production-grade, full-stack AI applications for clients using Gemini Enterprise and Google’s AI stack. Develop React interfaces, Python or Node.js services, agentic workflows, RAG pipelines, enterprise integrations, data pipelines, evaluations, and cloud infrastructure. Own solutions from interface through deployment, monitoring, and reliability testing. Collaborate directly with clients, support pre-sales, mentor engineers, and contribute to reusable engineering standards and accelerators.

Build and deploy production-grade, full-stack AI applications using Anthropic Claude, agentic workflows, MCP, RAG, and enterprise data integrations. Own interfaces, APIs, data pipelines, cloud infrastructure, evaluations, monitoring, and deployment. Partner directly with clients, communicate technical trade-offs, support pre-sales, mentor engineers, and establish engineering standards. The role requires strong Python and TypeScript/JavaScript skills, cloud experience, data engineering capabilities, and hands-on Anthropic ecosystem expertise.

Build and deploy full-stack AI applications, agentic systems, RAG pipelines, enterprise integrations, and production-grade OpenAI solutions. Own interfaces, backend services, data pipelines, infrastructure, evaluations, monitoring, and optimization. Deliver systems using OpenAI and Azure OpenAI, collaborate directly with clients, support presales, mentor engineers, and contribute to reusable engineering standards and accelerators.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Lead Clara’s global Customer Happiness organization across Mexico, Brazil, and Colombia. Responsibilities include developing regional leaders, defining customer experience strategy and KPIs, optimizing NPS, CSAT, SLAs, quality, and productivity, standardizing processes, and implementing AI-driven automation and self-service. The role partners with executive and cross-functional teams, uses customer data to identify friction, and ensures the organization has the talent, tools, capacity, and technology needed to scale.

Own the full sales cycle for Obvio’s AI-assisted traffic enforcement solutions across a national territory. Sell to state and local government agencies, navigate complex procurement and buying committees, build customer business cases, support pilots, and develop executive relationships. The role also contributes to sales playbooks, messaging, forecasting, pipeline management, and go-to-market processes while collaborating with product, engineering, marketing, and leadership.

Owns end-to-end LATAM marketing across Brazil and Mexico, including brand, demand generation, ABM, partner marketing, events, localization, customer case studies, and pipeline reporting. Partners with sales, account teams, HQ marketing, resellers, systems integrators, and platform partners to build regional programs and market presence. Translates complex AI and developer products into compelling messaging for enterprise buyers and technical audiences.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Leads fraud-domain pre-sales across Latin America, the Caribbean, and Brazil. Partners with clients to discover challenges, develop proposals, business cases, ROI studies, demonstrations, and executive presentations. Supports workshops, proof-of-concept engagements, negotiations, account planning, go-to-market strategy, and thought leadership. Applies expertise across transactional, identity, application, monitoring, KYC, internal, and first-party fraud while collaborating with sales and platform teams. Travel is required up to 50%.

Design and build the foundational AI platform infrastructure from scratch, including scalable architectures, guardrails, cost controls, observability, security mechanisms, and automation capabilities. The role requires operating high-scale distributed systems, managing Kubernetes and container platforms, implementing Infrastructure as Code and CI/CD, evolving databases, and influencing or mentoring other SREs. The position is remote-first within Brazil and involves multiple technical interview stages.

Build and deploy production-grade agentic AI and machine learning systems, including scalable backend services, data pipelines, RAG applications, and cloud infrastructure. Collaborate with ML engineers, data scientists, and clients to discover use cases, develop AI-powered products, optimize platform performance, and support deployments. The role also involves MLOps, model monitoring and versioning, automated testing, infrastructure management, research and development, and direct client engagement.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

Drive new business across named Bay Area technology accounts, including software, cloud, semiconductor, and platform companies. Build territory plans, self-source pipeline through outbound and partner channels, develop executive relationships, lead account strategy, sell consulting and AI-enabled ServiceNow services, manage sales cycles, maintain forecasts, and serve as a technology-sector subject matter expert.

Leads LATAM media strategy and end-to-end campaign execution, translating global priorities into locally relevant activations. Manages media agencies, budgets, partners, and campaign performance across Brazil and CASSA. Oversees measurement, testing, optimization, and actionable insights while aligning global and local teams. The role supports integrated campaigns across PlayStation hardware, software, services, peripherals, and third-party marketing.

The role involves collaborating with customers on data integration, enhancing product architecture, and improving reinforcement learning algorithms while ensuring long-term client success.

Join Artefact LatAm's Data & Consulting team to design and implement end-to-end analytics and ML solutions. Work across data collection, processing, EDA, model development and production, translate technical findings for business stakeholders, collaborate with consultants and engineers, and optimize models for performance and scalability under senior guidance.

Leads the technical direction of AI-powered full-stack applications, making architectural decisions across Python backends, modern frontends, data pipelines, agentic workflows, and LLM integrations. Builds scalable services and interactive interfaces, drives code quality through reviews and mentoring, collaborates with product, design, and QA, and advises stakeholders on emerging AI and web technologies.

Leads the technical direction of AI-powered full-stack applications, making architectural decisions across Python backends, modern frontends, data pipelines, agentic workflows, and LLM integrations. Builds scalable services and interactive interfaces, mentors engineers, conducts code reviews, promotes engineering best practices, and collaborates with product, design, and QA teams to deliver technical roadmaps and software solutions.

Scale Addri, an AI-powered conversational assistant, into Addi’s primary in-app interface for shopping, banking, credit, payments, and support. The role owns product launches, conversational quality, AI evaluation frameworks, trust and safety guardrails, grounding, escalation flows, roadmap strategy, and business-case development. Success includes improving resolution rates, customer satisfaction, task completion, conversion, and operational efficiency while ensuring accurate, compliant customer interactions.

Build and integrate LLM-powered software into enterprise systems. Design autonomous AI agents, tool-calling systems, and multi-step orchestration workflows using MCP or equivalent interfaces. Develop scalable backend architectures with REST/gRPC APIs, optimize context management, implement reliability patterns, and support systems from rapid prototyping through production. Collaborate in English with distributed teams during Central Time hours.

Build and deploy production AI agents, integrations, data pipelines, and applications within client environments. Lead discovery, translate business challenges into valuable solutions, establish evaluation and monitoring frameworks, and coordinate multidisciplinary delivery. Senior engineers lead executive discovery, own engagement outcomes, mentor peers, and create reusable implementation patterns. The role requires strong Python expertise, production LLM and agentic-system experience, cloud and enterprise integration skills, technical communication, and willingness to work onsite and travel approximately 25–50%.

Supports financial data extraction, quality checks, dashboard creation, report automation, metric documentation, forecasting preparation, and process documentation. The intern will use SQL, visualization tools, AI, and automation technologies to improve financial routines and solve business problems while learning in a data-focused SaaS environment.