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You will manage the end-to-end lifecycle of enterprise AI platform connectors, including configuration, security scoping, and identity synchronization. Additionally, you will automate deployment processes using CI/CD pipelines and Terraform while ensuring compliance with security and governance standards.
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.
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