AI Engineer & Software Architect

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Engineer & Software Architect based in Brazil.** This is a high-impact architecture role focused on turning validated AI prototypes into secure, scalable, and sustainable enterprise capabilities. You will define the technical foundations connecting AI models and prototypes with corporate data platforms, CRM systems, and enterprise LLM gateways. The role balances architectural rigor with pragmatism, prioritizing the shortest safe path from proof of concept to production. You will work across AI Engineering, Data Science, Product, Architecture, Security, and business teams in an environment of evolving requirements. A strong focus on privacy, compliance, open standards, and vendor-neutral design will be essential to long-term success. You will also evaluate scalability, integration complexity, resilience, and inference costs to support informed business decisions. This opportunity is ideal for a systems thinker who can bridge business needs, AI architecture, engineering realities, and sustainable technology strategy. ### Accountabilities - Design the conceptual architecture for AI prototypes and define practical paths for their evolution into scalable capabilities. - Assess technical and data feasibility in close collaboration with Data Science and AI Engineering teams. - Design and oversee secure integrations with corporate CRM platforms, behavioral and transactional data platforms, and enterprise LLM gateways. - Apply open orchestration standards and principles such as MCP and A2A to minimize vendor dependency and avoid unnecessary lock-in. - Document architectural decisions through clear Architecture Decision Records (ADRs), including alternatives, trade-offs, and rationale. - Ensure appropriate security, privacy, and data compliance practices, including PII masking, access controls, and decision auditing. - Collaborate with Product, Data Science, and business specialists to translate validated hypotheses into sustainable technical architectures. - Evaluate inference costs, scalability, and operational feasibility using FinOps principles to support Go/No-Go decisions. - Prepare comprehensive technical handoffs when validated initiatives move into scaled delivery. - Establish a pragmatic architecture that evolves with the product rather than over-engineering infrastructure before the prototype demonstrates value. - Contribute to the definition of success criteria during the first 90 days, including documented architecture, validated integrations, approved security and compliance practices, scale-cost estimates, and an objective recommendation for capability evolution. ## Requirements - Solid experience designing AI/ML system architectures for production or pre-production environments. - Strong knowledge of distributed systems, APIs, enterprise integrations, and architectural design principles. - Experience evaluating build-versus-buy-versus-prototype decisions and clearly communicating technical trade-offs. - Ability to design both conceptual and evolutionary architectures rather than focusing exclusively on a final-state solution. - Professional experience with cloud platforms such as GCP, AWS, or Azure. - Familiarity with data warehouses and lakes, data pipelines, and feature pipelines. - Experience integrating enterprise LLM gateways or multi-model proxies supporting providers such as OpenAI, Gemini, Claude, or equivalent. - Knowledge of vector databases and RAG architectures where appropriate. - Strong understanding of API security, SAST/DAST, data privacy, and regulatory requirements such as LGPD and GDPR. - Familiarity with zero-trust principles and vendor-neutral architecture strategies. - Experience using ADRs to maintain traceable architectural decisions without creating unnecessary bureaucracy. - Knowledge of MCP and A2A principles, with experience coordinating multiple specialized AI agents considered a strong differentiator. - Familiarity with technologies such as Vertex AI, SageMaker, Azure AI, BigQuery, Databricks, Snowflake, Kubernetes, CI/CD, and Infrastructure as Code is desirable. - Knowledge of RAG, function calling, embeddings, Generative AI, and Agentic AI is a plus. - Experience in B2B, mobility, fleet management, or regulated environments involving sensitive data is desirable. - Strong systems thinking and the ability to balance long-term architectural vision with short-term pragmatism. - Excellent communication skills, particularly the ability to explain complex technical decisions to non-technical stakeholders. - Comfortable working with ambiguity and evolving scopes across discovery, PoC, and capability-building stages. - Hands-on mindset with the ability to engage with real integrations rather than focusing exclusively on architectural diagrams. ## Benefits - Health insurance. - Dental insurance. - Meal and food allowance. - Childcare assistance. - Extended parental leave. - Access to fitness, health, and wellness professionals through Wellhub/Gympass and TotalPass. - Profit-sharing program (PLR). - Life insurance. - Continuous learning platform and professional development resources. - Discounts club and partner benefits. - Online platform dedicated to physical health, mental health, and overall well-being. - Pregnancy and responsible parenting courses. - Partnerships with online learning platforms. - Language-learning platform. - Remote work opportunity in Brazil. - Opportunity to work on innovative AI, architecture, and digital transformation initiatives. - Collaborative environment with strong opportunities for learning and cross-functional collaboration.