Platformscience
Cloud Infrastructure Engineer
Brazil
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hirly's read of this role
- Role family
- Supply chain
- Seniority
- Mid level
- Country
- BR
- Work mode
- Remote-friendly
- First seen by hirly
- 1 Sept 2026
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the posting
Cloud Infrastructure Engineer
Who We Are
At Platform Science, we’re working to connect everything that moves.
Founded in 2015, Platform Science is an open IoT platform partnering with innovative fleets, application developers, vehicle manufacturers, and equipment providers across the transportation industry. Our technology helps deliver modern solutions to supply chain professionals around the world.
Our employees bring diverse backgrounds, experiences, and perspectives. We believe great ideas can come from anywhere, and we foster a culture built around innovation, collaboration, empathy, resilience, and transparency.
About the Role
Platform Science is looking for a Cloud Infrastructure Engineer to join our CloudOps team.
CloudOps owns the foundational cloud infrastructure that enables our engineering teams to build, deploy, and operate products at scale. The team manages identity, networking, governance, security guardrails, backup, disaster recovery, and shared cloud services across a multi-account AWS environment spanning hundreds of accounts and multiple business units. We are also extending this operating model across Azure and GCP.
This is a hands-on senior individual contributor role for an engineer who enjoys building foundational infrastructure and solving complex cloud problems. You will own infrastructure and platform capabilities end to end, work primarily through Infrastructure as Code, and create guardrails and self-service capabilities that allow engineering teams to move quickly without sacrificing security or reliability.
The scope is intentionally broad. You may work on cloud identity and permissions, private networking, multi-cloud governance, backup and disaster recovery, security remediation, or developer self-service capabilities.
AI-assisted engineering is also part of how the team operates. We use AI coding agents to accelerate implementation and automation while maintaining rigorous engineering review, security, and production standards.
What You’ll Do
Own and evolve our multi-account AWS Landing Zone , including AWS Organizations, Control Tower, Account Factory for Terraform (AFT), organizational structures, Service Control Policies, tagging standards, and permission boundaries.
Extend cloud governance, operational standards, security controls, observability, and backup capabilities across AWS, Azure, and GCP .
Improve cloud identity and access management using least-privilege principles, including Okta federation, AWS IAM Identity Center, permission sets, group design, credential management, and reduction of standing privileged access.
Design and operate cloud networking capabilities, including IP address management, VPC architecture, routing, transit connectivity, Cloud WAN, egress architecture, and public/private DNS.
Help transition workloads from public-internet exposure to private and zero-trust networking models , including Kubernetes control planes, databases, and internal platforms.
Build self-service infrastructure capabilities for engineering teams, including account provisioning, environment provisioning, access requests, account lifecycle management, and infrastructure inventory.
Design and maintain backup, restore, and disaster recovery capabilities across cloud regions, accounts, and business units with different recovery requirements.
Implement immutable and ransomware-resistant backup strategies for cloud-native and managed third-party data platforms.
Build reusable Terraform/Terragrunt modules and infrastructure patterns that can be safely consumed by engineering teams across the organization.
Develop and maintain CI/CD automation for cloud infrastructure.
Partner with Security teams to investigate and remediate cloud security findings.
Partner with FinOps teams to identify cloud cost optimization opportunities that can be implemented broadly across the organization.
Build and maintain documentation, cloud standards, operating procedures, and shared responsibility models.
Use AI coding agents as part of the engineering workflow while maintaining ownership for requirements, architecture, testing, security, code review, and production outcomes.
Develop reusable prompts, context, workflows, and agent capabilities that improve the CloudOps team's productivity.
Required Experience
5+ years of professional experience in Cloud Infrastructure, DevOps, Site Reliability Engineering, Platform Engineering, Systems Engineering, or a related infrastructure discipline.
3+ years of hands-on experience with AWS or another major public cloud , with significant AWS experience strongly preferred.
1+ years of Infrastructure as Code experience , preferably using Terraform and/or Terragrunt.
Experience operating AWS at organizational scale, including AWS Organizations, multi-account architecture, and Control Tower or a comparable landing-zone architecture .
Production experience with at least one additional major cloud platform — Azure or GCP — beyond managing a single workload.
Strong experience designing reusable Infrastructure as Code modules and patterns consumed by other engineering teams.
Hands-on experience with cloud identity and access management, including SSO, SAML federation, SCIM provisioning, IAM policies, roles, permission boundaries, and least-privilege access models .
Strong cloud networking fundamentals, including IP address planning, VPC/VNet design, routing, transit architectures, DNS, private connectivity, and network security.
Experience designing or maintaining CI/CD pipelines using tools such as GitHub Actions, Jenkins, or similar technologies.
Experience scripting or programming with Python, Go, Bash, or similar languages .
Strong Linux fundamentals.
Working knowledge of Kubernetes and cloud-native infrastructure.
Experience using AI coding agents or AI-assisted development tools such as Claude Code, Cursor, Codex, or similar tools. Candidates should understand how to define requirements, establish success criteria, validate generated code, and identify situations where AI-generated infrastructure may introduce security or operational risk.
Ability to independently own complex infrastructure projects from design through production implementation.
Strong written and verbal communication skills with the ability to collaborate across Engineering, Security, FinOps, and other technical teams.
Advanced English proficiency.
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
Must reside in Brazil.
Preferred Qualifications
Experience with one or more of the following is highly desirable:
AWS Control Tower and Account Factory for Terraform (AFT)
AWS IPAM, Transit Gateway, or Cloud WAN
Multi-cloud governance across AWS, Azure, and/or GCP
Cross-account immutable backup and ransomware protection
MongoDB Atlas, Elastic Cloud, or similar managed data platforms
Wiz, GuardDuty, CrowdStrike, or other cloud security posture/security platforms
Zero-trust networking technologies such as Zscaler ZPA
Cloudflare WAF and DNS
Certificate and PKI lifecycle management using ACM, Private CA, cert-manager, or Let’s Encrypt
Agentic automation pipelines or automated remediation workflows
MCP servers or reusable AI agent skills
Secure access patterns and permission boundaries for AI-driven automation
Cloud cost optimization and FinOps
SOC 2 or comparable security/compliance frameworks
GitHub organization administration, including teams, apps, rulesets, and Actions runners
AWS, Azure, GCP, Terraform, Kubernetes, or related technical certifications
What Success Looks Like at the IC4 / P4 Level
A successful Senior Cloud Infrastructure Engineer at this level is expected to:
Independently own complex infrastructure projects.
Make sound technical decisions within established architectural direction.
Identify infrastructure risks and propose practical solutions.
Build reusable systems rather than one-off fixes.
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