Top Artificial Intelligence Jobs in Brazil

Own the execution layer for firm leadership by managing priorities, partner requests, planning cycles, meetings, decision briefings, stakeholder coordination, and initiative delivery. Design operating cadences, implement AI-enabled workflows, track commitments, resolve issues before escalation, and provide concise reporting to the Head of Firm Management. The role requires strong judgment, discretion, systems thinking, and the ability to act independently in a complex professional-services environment.

Lead the technical direction and development of Commure’s Insights practice management platform. Build scalable full-stack applications with React, Python, and PostgreSQL; improve reliability, observability, performance, and availability; collaborate across infrastructure, backend, product, and design teams; mentor engineers; lead high-impact projects; conduct code reviews; and drive architectural improvements for healthcare workflows serving thousands of practices.

As a Principal Data and AI Architect, you will design enterprise AI solutions, guide customer integration efforts, and conduct pre-sales workshops while ensuring best practices in architecture and data governance.

Provide technical leadership for agentic and LLM-based AI initiatives from problem definition through production. Design architectures involving orchestration, retrieval, tool use, state management, and external integrations. Establish evaluation, testing, observability, reliability, security, governance, and cost-management practices. Lead cross-functional initiatives, define reusable engineering standards, mentor engineers and technical leads, and communicate technical decisions to business and engineering stakeholders.

Design, build, deploy, and maintain AI-enabled applications for digital supply chain operations. Develop user interfaces, APIs, backend services, PostgreSQL databases, SQL queries, ETL/ELT pipelines, and integrations with BigQuery, SAP, and enterprise platforms. Implement LLMs, RAG, AI agents, and predictive models, while deploying containerized applications with Docker. Produce technical documentation and support production operations.

Responsible for selling partner solutions, acquiring new B2B customers, identifying opportunities, managing strategic partner relationships, conducting presentations and negotiations, generating leads through events, and closing deals. The role manages the sales funnel in HubSpot CRM, tracks performance against targets, collaborates with marketing, and contributes to process improvements.

Leads architectural strategy and complex software initiatives across Enterprise engineering domains. Designs scalable, secure, reliable systems; guides technical roadmaps, standards, design reviews, and platform improvements. Partners with cross-functional leaders, mentors senior engineers, identifies systemic risks, and establishes responsible AI-assisted development practices. Requires extensive experience with distributed systems, cloud-native platforms, microservices, and high-throughput production applications.

Own enterprise customers’ multi-year AI adoption roadmaps, guiding strategy, deployment, stakeholder alignment, responsible AI practices, and measurable business outcomes. Lead cross-functional teams across Product, Services, Sales, Success, and partners to accelerate time-to-value, increase automated resolution, improve retention, and drive expansion. Advise executives, analyze adoption and health metrics, coordinate technical escalations, and establish success plans, milestones, and ongoing engagement cadences.

Build and operate AI-assisted workflows that transform engineering information, support resolutions, and source changes into accurate, traceable documentation updates. Develop Python integrations, language-model workflows, validation checks, and review processes across source systems and publishing tools. Collaborate with engineering and documentation teams to resolve discrepancies, ensure revision applicability, and improve automation based on reviewer feedback.

Build and deploy practical AI-powered applications for clients using Python, Generative AI, LLMs, APIs, and cloud platforms. Collaborate with customers, product teams, and engineers to understand challenges, prototype solutions, integrate AI capabilities, and move features into production. Responsibilities include application development, testing, debugging, deployment, system integrations, AI agent workflows, solution architecture, and exploring technologies such as RAG, vector databases, MLOps, and AI observability.

Manages strategic private-sector accounts, drives new business, and expands customer relationships through consultative enterprise software sales. Responsibilities include identifying upsell and cross-sell opportunities, managing complex negotiations and deal closures, maintaining CRM pipelines and forecasts, developing account plans, monitoring competitors, and partnering with presales, specialists, inside sales, customer success, and ecosystem partners. The role focuses on revenue growth, customer satisfaction, market share, and positioning SUSE’s Linux, Kubernetes, cloud, edge, AI, and security solutions.

Lead the technical direction of an AI agent product, designing conversational AI, RAG pipelines, agent architectures, LLM evaluation, prompt management, monitoring, and observability. Develop proprietary machine learning models, productionize them with feedback loops, identify new AI use cases, and provide technical guidance across product teams. This hands-on role involves writing code regularly and partnering closely with Product in a remote Brazil-based environment.

Build and ship AI product features for Alti, including conversational AI, agents, automated routines, RAG pipelines, prompt strategies, and LLM evaluation systems. Establish monitoring and observability for AI features, help deploy ML models to production, and create continuous feedback loops. Collaborate with Product and Design to solve customer problems using AI and strengthen the team’s ML delivery practices.

Manage strategic public-sector accounts, identify new business and expansion opportunities, build executive relationships, and lead complex enterprise sales from prospecting through negotiation and close. Align SUSE’s Linux, Kubernetes, cloud, edge, AI, and security solutions with customer needs; maintain CRM pipelines and forecasts; develop account plans; monitor competitors; and collaborate with presales, partners, specialists, and customer success teams to drive revenue and long-term customer value.

Own the technical direction and development of Brex’s internal AI Agents Platform. Build production-grade agent capabilities, evaluation systems, secure integrations, and reliable asynchronous infrastructure. Partner with engineering, operations, and go-to-market teams to scale AI agents, improve developer experience, and support adoption. The role also includes operational ownership, incident response, technical mentoring, and roadmap leadership.

Product Manager responsible for shaping and executing the roadmap for an AI-powered personal assistant. The role involves analyzing user and business data, prioritizing cross-functional work, defining product requirements, measuring success, running experiments, presenting recommendations to leadership, and driving innovative B2C products. This is a hybrid role based in São Paulo, requiring fluency in English and Portuguese.

Develop and deploy enterprise AI applications, agents, copilots, generative AI solutions, RAG architectures, and business automations. Integrate AI with enterprise platforms, databases, APIs, CRM, ERP, and collaboration systems. Design intelligent workflows, optimize prompts and models, and collaborate with business and technical teams to deliver secure, scalable, production-ready solutions that improve productivity and business outcomes.

Drive organizational AI adoption by identifying automation opportunities, translating business needs into AI use cases, designing AI workflows, and advising stakeholders. Lead workshops, coaching, training, change management, proof-of-concepts, and responsible AI governance. Define adoption KPIs, dashboards, business cases, ROI measures, and continuous improvement initiatives while collaborating with technical, security, and compliance teams.

Drives organization-wide AI adoption by identifying use cases, designing AI-enabled workflows, advising stakeholders, and supporting automation initiatives. Delivers AI training, coaching, workshops, and change management while developing governance practices, adoption KPIs, dashboards, and ROI measurements. Partners with technical, security, and compliance teams on responsible AI implementation, pilots, process optimization, and continuous improvement.

Own and negotiate Firecrawl’s commercial agreements, including enterprise contracts, data licenses, vendor agreements, NDAs, and partnerships. Advise sales, business development, product, and engineering on data rights, privacy, security, intellectual property, indemnification, and liability. Build legal templates, playbooks, fallback positions, and approval processes while supporting compliance initiatives. Operate autonomously, escalate novel issues appropriately, and provide practical business-focused legal guidance in a fast-moving AI infrastructure company.

Lead Wellz’s AI-native operational transformation by selecting workflows for redesign, shipping AI agents into production, driving adoption, evaluating build-versus-buy decisions, defining success metrics, and reporting progress to executives. The role partners across Revenue, Commercial, Marketing, Finance, Clinical Operations, and Transformation while coordinating with Wellhub’s global AI leadership in a rapidly evolving, multi-market environment.

Lead Wellz’s AI-native operations transformation by identifying and rebuilding workflows around AI agents, owning AI program execution, driving adoption, evaluating build-versus-buy decisions, measuring ROI, and communicating progress to executives across global markets.

Lead client-facing AI transformation engagements from opportunity discovery through proof-of-concept adoption. Gather requirements, identify high-ROI use cases, build business cases and roadmaps, manage AI pipelines, and collaborate with engineering teams on prototypes using client data and LLM services. Secure executive buy-in, promote responsible AI governance, and transition successful solutions to production delivery teams.

Lead development of production-ready AI products and generative AI features. Architect backend systems, integrate LLM APIs, build retrieval and agentic workflows, convert APIs into tools, and own features from prototype through delivery. Collaborate with clients and teammates, improve internal AI tooling, mentor engineers, participate in hiring, estimate scope and timelines, and evaluate models based on quality and cost.

Build LLM-based AI agents for hardware design verification, integrate agents with enterprise platforms, and develop testing, safety, and human-in-the-loop mechanisms to improve reliability and prevent hallucinations. The role requires Python development, AI orchestration frameworks, prompt engineering, RAG, vector databases, Unix, and fluency in English and Portuguese. Preferred experience includes version control, C++, TCL, design verification, EDA, VLSI, Verilog, and VHDL.