Rox Partner

• Deploy, orchestrate, and maintain AI applications in high-availability production environments • Develop and maintain complex system integrations using REST/GraphQL APIs, API Gateways, and Load Balancers • Build data pipelines and processing workflows for AI applications using Python in AWS environments • Design, optimize, and support architectures based on Agentic AI and Agent-to-Agent (A2A) communication • Implement and support integrations using MCP (Model Context Protocol) • Evolve and maintain OCR pipelines and unstructured data extraction workflows using LLMs • Create, manage, and enhance advanced monitoring and observability dashboards to ensure model health, inference performance, application availability, and operational cost control using Grafana, Rancher, and related tools • Monitor and optimize AI applications in production to ensure scalability, stability, and operational efficiency • Identify and resolve performance issues, bottlenecks, and failures in AI pipelines • Collaborate with cross-functional engineering, data, architecture, and product teams

• Write, test, and maintain product or system code, contributing to design decisions and the implementation of solutions. • Debug, optimize, and fix issues in existing systems, ensuring high performance and reliability. • Apply design practices focused on scalability, consistency, and fault tolerance in critical applications. • Actively participate in defining architecture and development best practices. • Collaborate with other technical teams, clearly communicating requirements and solutions. • Work in environments that use containers, orchestration, and cloud services, ensuring efficient and secure operation.

• Develop and maintain end-to-end web applications, ensuring scalability and performance. • Collaborate directly with the Tech Lead and product team to translate technical requirements into efficient features. • Ensure code quality through development best practices and peer code reviews (Code Review). • Implement and maintain continuous integration and continuous delivery (CI/CD) pipelines to optimize the deployment cycle. • Design and maintain relational databases, ensuring data integrity and security.

• Definir, estruturar e liderar a implementação do modelo de Governança de Dados, considerando o nível de maturidade do ambiente e evoluindo práticas, processos e ferramentas • Desenvolver e implementar frameworks de governança utilizando ferramentas nativas de cloud (GCP e AWS), como Dataplex, Data Catalog, BigQuery, e seus equivalentes na AWS (Lake Formation, Glue Data Catalog, Athena/Redshift), garantindo escalabilidade e padronização • Garantir a conformidade com a LGPD, com foco em controle de acesso (IAM), mascaramento de dados e gestão de informações sensíveis • Estruturar e evoluir o catálogo de dados corporativo, promovendo descoberta, entendimento e uso eficiente dos dados por áreas de negócio e times técnicos • Implementar e acompanhar processos de qualidade de dados (Data Quality), com monitoramento contínuo e definição de métricas (completude, consistência, acurácia, etc.) • Mapear e documentar a linhagem de dados, desde sistemas de origem (LMS, ERPs acadêmicos) até camadas analíticas e dashboards, utilizando recursos como Dataplex/Data Catalog (GCP) ou Glue/Lake Formation (AWS) • Atuar de forma consultiva como ponte entre negócio e tecnologia (Acadêmico, Marketing, etc.), definindo dicionários de dados, regras de negócio e indicadores • Liderar iniciativas de estruturação de Data Warehouse e metadados, utilizando soluções como BigQuery (GCP) ou Redshift/Athena (AWS) • Propor e acompanhar um plano de evolução de governança, incluindo priorização de iniciativas, implementação e mensuração de valor para o negócio • Apoiar o uso de dados e iniciativas de IA/Analytics, garantindo qualidade, governança e confiabilidade das bases utilizadas

• Implement, administer and enhance PAM solutions (CyberArk), ensuring privileged access control and protection of critical credentials. • Manage privileged accounts, password vaults and access policies, with integration to Active Directory (AD) and other corporate systems. • Administer and optimize Fortinet Firewalls (FortiGate), including rule creation, review and troubleshooting. • Operate and advance XDR and SIEM solutions (Palo Alto – Cortex XDR / Data Lake), including alert tuning and development of use cases. • Investigate and respond to security incidents, perform root cause analysis and propose continuous improvements. • Structure and execute vulnerability assessment and management processes, prioritizing based on risk (CVSS) and tracking remediations. • Perform hardening of Windows and Linux servers, ensuring compliance with security best practices. • Monitor and analyze security logs and events in on-premises and cloud environments. • Work with Brand Protection solutions (Rainforest or similar), identifying and mitigating threats such as phishing and brand abuse. • Define, implement and evolve information security policies, standards and procedures. • Support audits and compliance initiatives (ISO 27001, LGPD, among others). • Act as a consultant to business and technology teams, promoting a security culture and risk management.

• Define, evolve and ensure adoption of data architectures on Azure, aligned with business strategy and industry best practices • Act as a technical reference on complex initiatives, supporting architectural and technology decisions • Lead implementation of large-scale data solutions using services such as Azure Data Factory, Azure Databricks and Azure Synapse • Establish standards, frameworks and data engineering best practices, ensuring quality, governance and security • Design, build and optimize data pipelines with a focus on performance, scalability and operational efficiency • Drive modernization and migration initiatives for data platforms to the cloud • Collaborate with business, architecture, security and engineering teams to ensure integrated and sustainable solutions • Serve as a technical mentor, supporting squads and sharing knowledge across the team • Analyze and optimize costs, performance and cloud resource utilization, driving continuous improvements

• Lead the development of complex user interfaces using React.js, ensuring the creation of reusable, high-performance components aligned with TypeScript best practices. • Make architectural decisions related to state management (Context API/Redux), API consumption (REST/GraphQL), and project organization, ensuring clean, maintainable code. • Foster a culture of quality within the team, owning the implementation of unit, integration, and E2E tests (Jest, Testing Library, and Cypress) to guarantee delivery stability. • Identify bottlenecks and drive performance optimizations to deliver a smooth and efficient user experience. • Act as a technical reference, performing constructive code reviews and supporting the team’s technical growth through mentorship. • Collaborate with Product and Design teams to translate business requirements into technical solutions, working autonomously in a remote environment. • Support the evolution of CI/CD pipelines, contributing to an agile, secure continuous integration and deployment process.

• Projetar e implementar soluções de Inteligência Artificial corporativas integrando Microsoft Copilot Studio, Power Apps, Power Automate e APIs de modelos OpenAI. • Definir padrões técnicos e arquiteturais para automações inteligentes e soluções baseadas em IA. • Desenvolver e manter aplicações em Python, com atuação em ambientes como Databricks. • Atuar em projetos de dados com conceitos de arquitetura Medallion (Medalhão), garantindo organização e governança dos dados utilizados pelas soluções de IA. • Criar e manter políticas de governança para o uso seguro, responsável e ético de IA. • Monitorar KPIs de adoção, impacto e conformidade das soluções implementadas. • Orientar equipes técnicas e de negócio sobre boas práticas de uso de IA e ferramentas como Copilot. • Conduzir workshops, treinamentos e sessões de capacitação para usuários avançados. • Atuar como referência técnica na disseminação de conhecimento sobre IA dentro da organização. • Identificar novos casos de uso e oportunidades de automação com IA. • Desenvolver business cases e análises de viabilidade para justificar investimentos em iniciativas de IA.

• Lead the design, development, and implementation of AI-driven software solutions using Azure AI Foundry, Azure OpenAI, and other Microsoft technologies. • Architect and develop multi-agent systems and advanced AI task orchestration/execution frameworks. • Design and integrate Graph Connectors, API Plugins, and Azure AI Search to support intelligent enterprise solutions. • Translate complex business requirements into scalable, secure technical architectures. • Act as the technical owner, ensuring the quality, performance, security, and maintainability of solutions. • Collaborate with cross-functional teams (engineering, product, UX, and business stakeholders) to deliver outcomes aligned with strategic objectives. • Establish and enforce development best practices, including code reviews, documentation, testing strategies, and technical standards. • Identify, diagnose, and resolve complex issues throughout the software development lifecycle. • Communicate clearly with technical and non-technical audiences, influencing decisions and driving alignment. • Mentor and support other engineers, contributing to the team’s technical maturity and continuous improvement.

• Lead the development of scalable, robust analytical models using DBT. • Ensure the implementation of modeling standards (dimensional and/or relational) and analytics engineering best practices. • Create, test and document transformations, ensuring data quality, reliability, traceability and governance. • Develop and maintain complex data pipelines using Airflow (or equivalent orchestration tools), applying versioning, modularity, observability and DataOps best practices. • Integrate different data sources (structured and unstructured), ensuring efficient, resilient and monitorable processes. • Optimize queries, structures and costs in cloud Data Warehouses (such as BigQuery, Redshift, Snowflake or similar), applying advanced performance tuning techniques. • Ensure governance, security, access control (IAM), partitioning, clustering and dataset versioning. • Collaborate with Data Analysts and Data Scientists to enable the consumption of reliable, well-documented and semantically organized datasets. • Evangelize technical standards, transformation best practices and governance across the organization. • Create and support dashboards and analytical products using BI tools (Looker, Power BI, Tableau or similar). • Work with Engineering, Product, Business and Data Governance teams to ensure data integration, consistency and quality. • Participate in defining and evolving modern cloud data architecture (GCP or AWS), proposing continuous improvements.