Cloud Infrastructure Specialist II

Description

Job Summary: This Cloud Infrastructure Specialist II will architect and evolve the AI platform infrastructure of Cloud TOTVS, ensuring security, scalability, and sustainability. Key Highlights: 1. Architect and evolve AI infrastructure with a GPU-first approach 2. Act as Tech Lead with autonomy and professional development responsibilities 3. Focus on reliability, continuous improvement, and platform-oriented thinking **Cloud Infrastructure Specialist II** ============================================== TOTVS | São Paulo | Remote Job Description Architect and evolve the AI platform infrastructure of Cloud TOTVS securely, scalably, and sustainably, ensuring operational predictability, financial efficiency, and low technological coupling to support the continuous growth of inference services and AI products across the company. Responsibilities and Duties * Architect and evolve inference infrastructure and support for model training and fine-tuning, applying a **GPU-first** approach, considering on-premises environments, cloud, and external services where applicable. * Define environment architecture, including network topologies, workload isolation, high availability, capacity, and resilience. * Plan and execute deployment of the AI platform, ensuring compatibility among hardware, operating systems, drivers, CUDA stacks (or equivalents), Kubernetes, and inference platforms. * Operate and maintain the production inference platform, ensuring availability, performance, and operational continuity (within strategic architecture scope). * Support planning and execution of improvements arising from complex incidents involving GPUs, Kubernetes, networks, storage, and inference workloads. * Apply SRE practices, including definition and monitoring of SLOs, SLIs, error budgets, and incident management. * Operate and evolve commercial and open-source inference stacks (e.g., NVIDIA AI Enterprise, Triton, vLLM, KServe), ensuring portability and mitigation of vendor lock-in. * Define and standardize usage of inference services where applicable (e.g., Triton, NIM). * Architect and operate Kubernetes clusters for AI workloads, focusing on multi-tenant isolation, GPU scheduling, concurrency, queuing, backpressure, and scalability. * Implement full-stack observability covering infrastructure, GPUs, Kubernetes, and inference services. * Ensure visibility into resource consumption, capacity, operational risks, and financial impact of AI workloads. * Support capacity planning and budgeting processes, evaluating trade-offs between commercial and open-source solutions. * Integrate DevSecOps practices from platform conception through operation. * Ensure compliance with security policies, auditing requirements, access control, and environment segregation. * Disseminate technical standards, best practices, and knowledge through structured documentation and technical mentoring. * Provide technical support to internal forums and decision-making processes related to AI infrastructure. Requirements and Qualifications **Experience** * Minimum 5 years of experience in IT infrastructure, cloud, or distributed platforms, working in mission-critical environments. * Proven experience in architecture and operation of distributed systems, preferably with data, analytics, or AI workloads. * Minimum 3 years of experience in cross-functional teams, collaborating with product, data, security, and architecture teams. **Academic Background** * Bachelor’s degree in Information Technology, Engineering, Computer Science, or related fields. * Postgraduate degree or MBA in Software Architecture, Cloud Computing, Distributed Systems, Information Security, or related areas (desirable). **Languages** * Advanced English proficiency for technical reading, writing, and speaking, with ability to participate in technical and strategic discussions. **Certifications (Preferred)** * Certifications related to Kubernetes, Public Cloud, and Infrastructure as Code (IaC). **Specific Knowledge / Skills** * Proficiency in distributed systems, including concurrency, load balancing, workload isolation, queuing, and backpressure. * Solid Kubernetes experience, including managed environments (EKS, GKE, AKS), advanced scheduling, and multi-tenant isolation. * Advanced knowledge of mission-critical environments, with focus on high availability, resilience, and operational continuity. * Mastery of networking architecture applied to cloud and Kubernetes (TCP/IP, DNS, Load Balancers, Firewalls, SDN). * Expertise in applying storage solutions for I/O-intensive workloads in Kubernetes and large-scale environments. * Experience with public cloud services (AWS, Azure, and/or GCP) and understanding of the shared responsibility model. * Mastery of observability (metrics, logs, traces) applied to infrastructure and AI platforms. * Experience with Infrastructure as Code (IaC) and automation. * Applied knowledge of DevSecOps and SRE practices. Desirable Requirements * Strong sense of ownership over the platform and its outcomes. * Ability to resolve complex infrastructure and distributed system issues. * Clear and structured communication with technical audiences, with ability to translate technical impacts into operational and financial risks. * Decision-making guided by technical, operational, and cost trade-offs. * Mindset oriented toward reliability, continuous improvement, and platform thinking. * High analytical capability for diagnosing and resolving complex problems. * Understanding of business context to inform technical decisions. * Proactive and results-oriented attitude. * Collaborative profile with ease of interaction in multidisciplinary environments. * Will work within the **Core Infrastructure** area, part of the Infrastructure organization within the Cloud ecosystem. * This area has a foundational role, making decisions that impact the entire company—especially in defining the strategic cloud architecture. * The professional will act as **Tech Lead**, with autonomy to independently drive initiatives and responsibility for supporting and developing other professionals, including specialists. * Must demonstrate strong learning, unlearning, and teaching capabilities, keeping pace with the continuous evolution of the Cloud environment—with current strategic focus on AI and distributed architecture. Salary Range To be determined Employment Type CLT Benefits * TOTVS Network University: A corporate university offering free content and certifications for all TOTVS employees; * +Healthy Program: Supports each TOTVER with advisory services and initiatives focused on physical, mental, and personal financial wellbeing; * +Advantages Program: Latin America’s largest discount network, exclusively for our employees; * +Care Program: Personal support program for employees and their families, offering guidance across multiple specialties including psychology, social work, pet consultation, etc.; * Einstein Conecta: Free online medical consultation service provided by physicians from Hospital Israelita Albert Einstein; * Health and dental insurance; * Meal and/or food allowance; * Transportation allowance and shuttle services at select metro stations; * Extended maternity and paternity leave; * Nursing room; * Bicycle parking; * Changing rooms; * Life insurance; * Childcare allowance; * Private pension plan; * Office designed to foster creativity and productivity, featuring snack areas, game rooms, billiard tables, and relaxation chairs; * Gympass. About the Company As a technology leader, we are a community of non-conformists driven by innovation, autonomy, learning, and performance. Together, we create opportunities, transform futures, and share knowledge. Your professional development happens here in an inclusive, respectful, and energizing environment — people empowering people! We pursue sustainable growth, leveraging data and AI to deliver smarter, more efficient outcomes for our customers. Join us to innovate and build the future of technology. \#VemPraTOTVS \#SomosTOTVS