Top Artificial Intelligence Jobs in Brazil

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.

Designs, develops, deploys, and maintains production-grade AI and machine learning solutions for healthcare and life sciences. Builds Generative AI, LLM, RAG, semantic search, agentic AI, and workflow orchestration applications. Develops cloud-native platforms, APIs, MLOps pipelines, and reusable AI frameworks while ensuring scalability, security, governance, and compliance. Partners with clients and technical stakeholders to translate business challenges into solutions using healthcare data, communicates insights to executives, mentors junior engineers, and supports AI innovation.

Designs, develops, and scales secure, production-grade Generative AI and Agentic AI applications. Responsibilities include building agent solutions, Python tooling, RAG pipelines, sandboxed execution environments, MCP integrations, observability, evaluation frameworks, human-in-the-loop workflows, prompt and model management, and cost optimization. Collaborates with data, analytics, platform engineering, and business teams to deliver reliable enterprise AI solutions.

Leads Johnson & Johnson’s enterprise HR AI and automation strategy across the Hire-to-Retire lifecycle. Oversees teams delivering generative AI, conversational AI, machine learning, RPA, and workflow solutions; establishes product roadmaps, governance, adoption strategies, KPIs, and value realization measures. Partners with HR, IT, product, and business leaders to improve employee experiences, simplify processes, reduce manual effort, and drive global digital transformation. The role also requires executive influence, responsible AI oversight, and leadership of innovation-focused teams.

Leads Johnson & Johnson’s enterprise HR AI and automation strategy across the Hire-to-Retire lifecycle. The role manages teams delivering generative AI, conversational AI, machine learning, workflow orchestration, and RPA capabilities; partners with HR, IT, product, and business leaders; establishes roadmaps and governance; drives adoption and transformation; and measures business value, employee impact, and operational outcomes.

Design and build AI agentic systems that collaborate with developers across the SDLC, including planning, coding, testing, deployment, LLM integration, tool use, orchestration, reasoning loops, and context management. Architect scalable distributed systems on AWS, evaluate .NET and other ecosystems, and guide engineering teams in production implementation.

Annotate, evaluate, and curate text, video, and geographic data to train and improve AI and machine learning models. Follow detailed guidelines, conduct basic research, maintain annotation quality, identify data patterns, provide process feedback, meet deadlines, and adapt to evolving instructions. The role is full-time and remote in Brazil, with one required visit to the São Paulo office to collect equipment.

Early-career engineer role building AI-driven features, prototypes, and production-quality systems using modern AI coding agents. Work closely with founders and senior engineers to iterate fast, direct and evaluate AI agents, and contribute to AI infrastructure and agentic development workflows.

Lead development of AI-native production systems: convert AI-assisted prototypes into scalable, secure software; own architecture, reliability, and technical direction; direct and control AI coding agents; define engineering standards and workflows; collaborate with founders on product and strategy; debug complex issues and elevate engineering quality.

Create high-volume, high-quality marketing content using generative AI and AI agents (video, image, social). Develop timely campaign ideas, track AI and cultural trends, experiment with formats, and work closely with founders and the marketing team to shape brand voice and growth.

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.

Design, build, evaluate, and deploy production-grade LLM and classical ML solutions. Create retrieval and agentic workflows, integrate AI into client apps, implement evaluation frameworks, optimize prompts and pipelines, and collaborate with product teams through discovery to production support.

Design and build AI-powered IT help desk automation using AWS Bedrock and serverless tech. Develop AI agents for ticket triage, routing, IAM automation, REST integrations with enterprise systems, and scalable cloud-native architectures. Collaborate on architecture, integrations, and agent performance improvements.

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.

Design, implement, and maintain gameplay AI systems for Fortnite. Collaborate with designers, artists, and engine teams to prototype, optimize, and ship AI features, fix bugs, and ensure high-quality cross-platform experiences.

Architect and build production AI-powered HR systems using agentic workflows, multi-agent systems, APIs, and workflow automation. Integrate Workday and other HR tools, implement governance, audit logging, privacy controls, and human approval gates, and ensure reliable payroll-adjacent workflows. Document solutions, train People team users, drive adoption, and measure automation impact. The role requires strong software engineering, AI application development, HR technology, Workday, data privacy, and workflow automation experience.

Designs and implements automation and AI solutions to transform Finance processes across Brazil, Spain, and Mexico. Responsibilities include mapping processes, identifying bottlenecks and control gaps, redesigning workflows, deploying AI use cases, reducing manual work, improving management information, and partnering with Finance, Technology, and Data teams to deliver scalable solutions. Success is measured through efficiency, accuracy, faster cycle times, stronger controls, and improved business insights.

Leads and develops a team of senior Data and AI Architects while setting architectural standards across enterprise data, AI, integration, identity, security, governance, and trust. Advises strategic customers and senior executives on architecture decisions, partners with Sales, Product, Engineering, and delivery teams, and connects technical recommendations to measurable outcomes. The role also builds reusable architectures, technical enablement, customer insights, and talent programs while driving operational rigor, adoption, and revenue impact.

Deploy and operationalize AI agents across global operations: build single and multi-agent systems, implement RAG/knowledge layers, evaluation, guardrails, observability, and own outcomes and budgets.

Design, build, and ship AI-native internal tools, dashboards, and automations using Claude Code. Develop n8n workflows, Next.js/Vercel apps backed by Supabase/Postgres, produce technical designs, prompt engineering, and train teams to adopt AI-augmented processes across the business.

As an AI Engineer at Vega, you'll design and implement AI systems, develop LLM-based applications, and optimize AI performance for cybersecurity solutions.

Design, build, deploy and maintain production software systems that embed LLMs and agentic AI. Develop scalable services, APIs, integrations, RAG/agent workflows, prompt engineering frameworks, monitoring and CI/CD. Operationalise models, optimise cost/performance, and collaborate with data scientists and business teams to deliver measurable AI-enabled products and decision-support solutions.