AI Platform Engineer
At a glance
Mid-level ML Platform & Ops role at Curotec. Remote, Brazil · contract.
Pay not stated AI Platform Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Take connector and skill requests from intake through permissions, identity sync, testing, documentation and requester handoff
- Set up platform features for the right users, choosing organization-wide or group-level access and applying suitable permissions
- Review outside skills, plugins and connectors for unsafe dependencies, prompt injection and data exposure risks
- Automate configuration and provisioning with Terraform and CI/CD, including deployments across development, staging and production
- Coordinate with security, identity, governance and business teams to keep AI features compliant
What you bring
- At least six years in platform or cloud engineering, DevOps, or enterprise systems administration
- Hands-on administration of Claude Enterprise, Microsoft 365 Copilot or Gemini Enterprise
- Strong Terraform skills, plus experience creating and maintaining CI/CD pipelines
- Practical IAM knowledge covering access groups, identity synchronization, SSO and SCIM provisioning
- Experience securing AI capabilities and working in large enterprises with strict compliance needs
Who this fits
This mid-level contractor role suits an engineer who combines enterprise platform operations with identity, security and automation work. It is remote and based in São Paulo, Brazil.
From the employer
We are a globally leading software services company specializing in developing enterprise-level projects for clients worldwide.Our team is a unique blend of diverse skill sets, cultures, and backgrounds—a true melting pot of talent. One of the most rewarding aspects of working at Curotec is the opportunity to learn something new every day, not just about technology but also about our amazing team members.
Visit our website to discover more about who we are and what we do.
Curotec is hiring AI Platform Engineers to support a large enterprise client in deploying, securing, and enabling its enterprise AI platforms. The engineers will take ownership of one strategic platform, whether Claude, Microsoft Copilot/Copilot Studio, or Google Gemini, while bringing cross-platform knowledge and a broader understanding of the enterprise AI ecosystem. You will work at the intersection of platform engineering, identity and access management, security, and automation, owning requests from intake through closure and ensuring that every AI capability is securely configured, appropriately scoped, thoroughly tested, and well-documented.
What You Will Do:
Own data connector and skill requests end-to-end, from intake through access group creation, identity provider synchronization, connector registration, per-tool permission scoping, testing, documentation, and closure with the requester.
Configure and distribute platform capabilities (skills, plugins, agents, connectors) to the right audiences, choosing between enterprise-wide and group-scoped distribution, with a clear understanding of scoping and permission controls.
Conduct security and quality reviews of third-party and externally authored skills, plugins, and connectors before release. This includes assessing dependencies and bundled scripts, and evaluating exposure to prompt injection and data exfiltration.
Replace manual console configuration with automated setup, registration, and provisioning through CI/CD pipelines and Terraform.
Build parameterized deployments across development, staging, and production environments.
Partner with the client's security, identity, governance, and business teams to keep AI capabilities compliant.
6+ years of experience in platform engineering, cloud engineering, DevOps, or enterprise systems administration.
Hands-on experience administering and configuring at least one of: Claude Enterprise, Microsoft 365 Copilot / Copilot Studio, or Gemini Enterprise.
Solid understanding of identity and access management: access groups, identity provider synchronization (Entra ID, Okta, Google Cloud Identity), SSO, and SCIM provisioning.
Experience configuring connectors between SaaS platforms and enterprise data sources (SharePoint, Google Drive, Confluence, Jira, Salesforce, ServiceNow, databases, internal APIs).
Strong Terraform skills.
Experience building and maintaining CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI, Cloud Build, or similar).
Working knowledge of AI-specific security risks such as prompt injection, data exfiltration, over-permissioned tools, and supply-chain risks.
Experience in large enterprise environments with strict security and compliance requirements.
Clear written communication and strong documentation habits.
Nice to Have:
Experience across two or more of the three platforms.
Experience with the Model Context Protocol (MCP), including building, deploying, or reviewing MCP servers.
Experience authoring or reviewing Claude Skills/Plugins, Copilot Studio agents and plugins, or Gemini Enterprise agents.
Scripting in Python, TypeScript, PowerShell, or Bash.
Familiarity with dependency scanning and code review tools (Snyk, Dependabot, SAST).
Background in regulated industries, especially life sciences or healthcare.