Staff DevOps Security Engineer in Brazil, Indiana at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff DevOps Security Engineer based in Brazil.

This role sits at the intersection of cloud infrastructure, security engineering, and platform reliability within a high-scale, AI-driven data and advertising technology environment. You will act as a senior technical leader responsible for designing, scaling, and securing multi-cloud infrastructure across AWS and GCP, while enabling fast and reliable delivery of data-heavy and machine learning workloads. The position combines deep DevOps expertise with a strong security execution mandate, embedding compliance and DevSecOps principles directly into engineering workflows. You will also help shape SRE practices, improving system observability, incident response, and operational resilience across global services. Working closely with engineering, data science, and product teams, you will ensure infrastructure is both highly automated and production-ready at scale. This is a hands-on leadership role for someone who thrives in fast-moving environments and actively leverages AI to improve infrastructure operations and efficiency.

You will be responsible for architecting, securing, and scaling cloud infrastructure while driving reliability, automation, and operational excellence across a global platform.

• Architect and scale multi-cloud infrastructure across AWS (primary) and GCP, supporting large-scale AI and data workloads
• Lead DevSecOps execution by implementing security controls, SOC 2 compliance requirements, and cloud security best practices
• Define and drive SRE practices, including SLO/SLI monitoring, incident response, postmortems, and error budget frameworks
• Build and optimize CI/CD pipelines using GitLab and GitOps methodologies to ensure safe and efficient deployments
• Design and implement observability solutions using metrics, logs, traces, and monitoring tools to improve system reliability
• Support and optimize MLOps infrastructure for machine learning pipelines and model deployment across platforms such as Vertex AI and SageMaker
• Manage containerized workloads using Kubernetes (EKS/GKE) and ECS with a focus on scalability and self-healing systems
• Collaborate across engineering, product, and data teams to ensure clear execution, dependency alignment, and architectural clarity
• Automate infrastructure processes and integrate AI-driven tools to reduce operational toil and improve delivery speed

You are a senior-level infrastructure engineer with strong DevOps, cloud architecture, and security expertise, capable of leading complex systems in high-scale environments.

• 8+ years of experience in DevOps, Cloud Engineering, or SRE roles in SaaS or data-intensive environments
• Strong expertise in AWS with working knowledge of or ability to quickly ramp on GCP
• Proven experience implementing SRE principles including SLOs, SLIs, on-call practices, and incident management
• Deep experience with CI/CD pipelines, especially GitLab, and strong proficiency in Infrastructure as Code (Terraform preferred)
• Solid understanding of observability tooling such as Datadog, Prometheus, Grafana, and OpenTelemetry
• Hands-on experience with Kubernetes and container orchestration in production environments
• Experience building or supporting MLOps pipelines and infrastructure for ML workloads is highly valued
• Strong background in DevSecOps practices and cloud security implementation, including compliance frameworks like SOC 2
• AI-forward mindset with active use of AI tools to improve engineering efficiency and automation
• Strong communication skills with ability to document architecture decisions and align cross-functional teams
• Fluent English (B2+ or higher) required for daily collaboration
• Experience in AdTech, MarTech, or high-volume data platforms is a strong plus

• Competitive annual compensation with equity package
• Fully remote role across Brazil and other LATAM countries
• Opportunity to work on large-scale AI and data infrastructure systems
• Exposure to multi-cloud environments (AWS and GCP) and cutting-edge ML platforms
• High-impact engineering role with strong ownership and technical leadership scope
• Collaborative global team working in English across engineering and data science functions
• Involvement in architectural decisions shaping platform scalability and security
• Culture that values automation, pragmatism, and engineering excellence