Arquiteto de Software​

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Arquiteto de Software based in Brazil.** This role offers the opportunity to serve as the technical architecture reference for a team building a data-driven platform focused on risk and control monitoring. You will shape robust, scalable, flexible, and maintainable solutions across cloud-native and Generative AI environments. The position combines hands-on architectural design with technical leadership, helping developers make sound implementation decisions. You will define technical patterns for AI agents, orchestration, integrations, memory, context, and asynchronous communication. Security, compliance, resilience, efficiency, and architectural governance will be central to your work. This is an environment where innovation, engineering excellence, and business objectives come together to build modern technology capabilities at scale. ### Accountabilities: - Translate architectural solutions into detailed implementation designs, producing Low Level Designs and providing technical guidance to software developers on complex design and implementation decisions. - Act as a technical reference and knowledge multiplier for the team, promoting standardized development practices, reusable platformization patterns, and architectural frameworks that improve engineering productivity. - Define the technical architecture for AI agents, including agent harness patterns, orchestration strategies, tool integrations, memory and context mechanisms, and multi-agent architectures. - Ensure that applications meet agreed non-functional requirements related to security, compliance, resilience, performance, efficiency, and other architectural governance standards. - Guide engineering teams in evaluating business objectives, architectural trade-offs, quality attributes, technical risks, and long-term implications before making software design decisions. - Design and detail integration flows and asynchronous messaging architectures, ensuring secure and reliable data movement across high-volume environments. - Establish and maintain reference architecture documentation, ensuring that technical decisions, standards, and reusable patterns remain accessible and up to date. - Manage the technology lifecycle of solutions by identifying and preventing the adoption of obsolete technologies and supporting the management of architectural debt. - Work closely with Solution Architecture and participate in architecture forums, contributing technical expertise to broader architectural decisions and governance processes. ### Requirements - Solid professional background as a Senior Software Engineer or Software Architect, with demonstrated experience designing and operating scalable, cloud-native systems. - Advanced development skills in Python, including experience with modern frameworks and contemporary software engineering practices. - Hands-on experience designing and operating solutions on Google Cloud Platform (GCP), including GKE (Google Kubernetes Engine), Cloud Run, Cloud Functions, and Secret Manager. - Practical experience architecting Generative AI solutions involving LLMs, Retrieval-Augmented Generation (RAG), and agent frameworks such as LangChain, LangGraph, CrewAI, or equivalent technologies. - Strong knowledge of AI agent architecture, including agent harness patterns, orchestration, tool integration, memory and context management, and multi-agent approaches. - Deep understanding of Event-Driven Architecture (EDA), with practical experience using asynchronous messaging platforms and buses, preferably Apache Kafka. - Experience designing, structuring, and consuming RESTful APIs, together with knowledge of secure data transport and payload protection patterns. - Familiarity with technology obsolescence governance and processes for identifying, registering, and managing architectural debt. - Strong understanding of software architecture principles, including scalability, maintainability, resilience, security, and non-functional requirements. - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. - Experience with Vertex AI, including Agent Builder and Model Registry, as well as GenAIOps or LLMOps practices such as prompt and model versioning, monitoring, and cost and token tracking, is a strong advantage. - Knowledge of data security practices for microservices, including mutual TLS and secure credential management through secrets vaults, is considered a plus. - Experience with agent evaluation frameworks and LLM observability tools such as LangSmith, Langfuse, or equivalent platforms is desirable. - GCP Professional Cloud Architect or Professional Cloud Developer certification is considered an additional advantage. ### Benefits - Opportunity to work on a modern technology platform combining data, automation, cloud-native architecture, and Generative AI. - High technical ownership and influence over architecture standards, development patterns, and technology decisions. - Exposure to advanced AI agent architectures, LLMs, RAG, orchestration, and emerging GenAI engineering practices. - Opportunity to contribute to scalable, resilient, secure, and high-volume technology solutions. - Collaboration with software engineering and solution architecture teams in a technically challenging environment. - Opportunity to act as a technical reference and contribute to the evolution of engineering practices and architectural maturity.