Devops /Platform Engineer in Brazil, Indiana at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a DevOps / Platform Engineer in Brazil.

This role is a high-impact opportunity to design and operate the foundational infrastructure powering large-scale digital and AI-driven systems within a global enterprise environment. You will build and evolve cloud-agnostic platforms that enable engineering teams to deliver applications, microservices, and machine learning models with speed, reliability, and security. The position combines traditional DevOps, platform engineering, and advanced MLOps responsibilities, making it central to the organization’s AI transformation journey. You will design scalable CI/CD pipelines, robust Kubernetes-based infrastructure, and developer-friendly platforms that accelerate delivery across teams. A strong emphasis is placed on automation, observability, and operational excellence across multi-cloud environments. You will also play a key role in shaping how AI models are deployed, monitored, and managed in production. This is a highly collaborative and technical role within a fast-evolving, globally distributed engineering organization.

• Design, implement, and maintain end-to-end CI/CD pipelines supporting applications, infrastructure-as-code, data pipelines, and AI/ML model deployments.
• Build and manage cloud-agnostic infrastructure across AWS, Azure, and/or GCP, ensuring scalability, portability, and reliability.
• Develop and operate Kubernetes-based environments for containerized workloads, including microservices and AI model serving systems.
• Implement Infrastructure-as-Code solutions using Terraform or similar tools to create reusable, modular, and secure infrastructure components.
• Lead MLOps initiatives, including model training environments, deployment pipelines, model registries, and production monitoring systems.
• Establish observability, reliability, and security practices, including monitoring, logging, alerting, and incident response frameworks.
• Design and support internal developer platforms to improve self-service infrastructure provisioning and developer experience.
• Drive cloud cost optimization, security automation, and compliance alignment across distributed environments.

• 6+ years of experience in DevOps, SRE, or platform engineering roles, including at least 2 years supporting AI/ML production workloads.
• Strong expertise in infrastructure-as-code tools such as Terraform, with knowledge of cloud-native alternatives (Pulumi, CloudFormation, Bicep).
• Hands-on experience with Kubernetes (EKS, AKS, or GKE), including cluster operations, scaling, and troubleshooting.
• Solid experience designing and maintaining CI/CD pipelines using tools such as GitHub Actions, GitLab CI, Azure DevOps, or Jenkins.
• Strong cloud experience across at least two major providers (AWS, Azure, GCP), including networking, compute, storage, and IAM.
• Proficiency in scripting and automation using Python, Bash, or PowerShell, and familiarity with Go or TypeScript is a plus.
• Experience with observability stacks (Prometheus, Grafana, Datadog, ELK, OpenTelemetry) and incident management tools.
• Strong understanding of security best practices, including secrets management, IAM, container security, and compliance automation.
• Experience with GitOps workflows (ArgoCD, Flux) and modern platform engineering practices.
• Excellent communication skills and ability to work effectively in global, multicultural teams.

• 100% remote work model (Brazil-based role).
• Competitive contractor-based compensation (PJ model).
• Opportunity to work on large-scale, global, AI-driven infrastructure systems.
• Exposure to cutting-edge technologies in DevOps, MLOps, and platform engineering.
• Collaborative international environment with cross-functional engineering teams.
• Strong focus on professional growth, technical leadership, and continuous learning.
• Work within a regulated, enterprise-grade environment with high technical standards.
• Opportunity to influence platform strategy and shape AI infrastructure at scale.