Cloud/Security Engineer, AI Platform
Ultimus Fund Solutions
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- Pay
- $100K to $250K
- a year
- Location
- Columbus, OH
- Work style
- On-site
- Job type
- Other
- Posted
- Nov 7
- 1 day ago
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Career path
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About the company
Ultimus Fund Solutions
Financial services · 501 to 1,000 employees
What you'll do
- Design and operate the Azure cloud environment for the AI platform
- Implement identity and access for people, applications and AI agents
- Build security controls into the platform
- Implement AI guardrails and policy enforcement
- Monitor for threats and misconfigurations, respond to security events and support audits
- Manage cloud cost and capacity for AI workloads
Key skills
Azureidentity and accessleast-privilege permissionssecrets managementencryptiondata loss preventionAI guardrailspolicy enforcementsecurity events
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About the team
Ultimus is investing in AI to transform how fund administration work gets done, from generative AI assistants, intelligent document processing and machine learning to a growing set of agentic AI workflows. The AI Infrastructure team builds and runs the secure, shared platform that all of our AI solutions are built on, giving teams across the firm a consistent, well-governed foundation for building, deploying and scaling AI applications, models and agents. You will join early and help shape the platform and practices the rest of the firm builds on.
About the role
As Cloud / Security Engineer you make sure our AI platform is secure, compliant and well run in Azure, with the right identity, access, data protection and guardrails for the AI applications, models and agents that work with sensitive client data.
What you'll do
Design and operate the Azure cloud environment for the AI platform: subscriptions, networking, private endpoints and landing zones.
Implement identity and access for people, applications and AI agents, including agent identities, least-privilege permissions and on-behalf-of access to source systems.
Build security controls into the platform: secrets management, encryption, data loss prevention, sensitive-data handling and an agent kill-switch.
Implement AI guardrails and policy enforcement in partnership with Compliance, Risk and Information Security.
Monitor for threats and misconfigurations, respond to security events and support audits and client due diligence.
Manage cloud cost and capacity for AI workloads.