Senior Manager, Infrastructure & AI Engineering
Free account needed to apply or save. It takes a minute, and we'll bring you right back to this job.
How well do you match this job?
Key details
- Location
- Columbus, OH, United States
- Work style
- Onsite
- Level
- Lead / Staff+
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- 12h ago
Skills
data governancedue diligencefund administrationgenerative aimachine learningmodel context protocolsnowflake
About the role
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 Senior Manager, Infrastructure & AI Engineering, you lead the AI Infrastructure team: a Solution Architect, DevOps Engineers and Cloud / Security Engineers who build and run the shared platform our AI applications, models and agents depend on. You own the team, the platform roadmap and day-to-day delivery, and you make sure the AI Development pods have a reliable, secure and well-governed foundation to build on.
What you'll do
Lead, hire and develop the AI Infrastructure team (Solution Architect, DevOps Engineers and Cloud / Security Engineers), setting clear goals, priorities and engineering standards.
Own the AI platform roadmap and delivery plan with the Solution Architect, turning the target architecture into sequenced, well-planned work.
Run the platform as a production service: reliability targets, monitoring, incident and change management, release controls and the agent kill-switch process.
Make sure the AI Development pods can build, test and release AI solutions quickly on the shared platform, and resolve priorities and dependencies across teams.
Oversee the platform's shared data foundation, including Snowflake integration, vector and document stores and MCP servers, working with the pod data engineers and the data governance team.
Partner with Information Security, Compliance and Risk so the platform meets our regulatory, data-protection and audit requirements, and support client due diligence.
Manage the platform budget, cloud and model-usage costs, and vendor and partner relationships, including knowledge transfer from external partners during the initial build.
Report platform status, risks and metrics to AI program leadership.
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 Senior Manager, Infrastructure & AI Engineering, you lead the AI Infrastructure team: a Solution Architect, DevOps Engineers and Cloud / Security Engineers who build and run the shared platform our AI applications, models and agents depend on. You own the team, the platform roadmap and day-to-day delivery, and you make sure the AI Development pods have a reliable, secure and well-governed foundation to build on.
What you'll do
Lead, hire and develop the AI Infrastructure team (Solution Architect, DevOps Engineers and Cloud / Security Engineers), setting clear goals, priorities and engineering standards.
Own the AI platform roadmap and delivery plan with the Solution Architect, turning the target architecture into sequenced, well-planned work.
Run the platform as a production service: reliability targets, monitoring, incident and change management, release controls and the agent kill-switch process.
Make sure the AI Development pods can build, test and release AI solutions quickly on the shared platform, and resolve priorities and dependencies across teams.
Oversee the platform's shared data foundation, including Snowflake integration, vector and document stores and MCP servers, working with the pod data engineers and the data governance team.
Partner with Information Security, Compliance and Risk so the platform meets our regulatory, data-protection and audit requirements, and support client due diligence.
Manage the platform budget, cloud and model-usage costs, and vendor and partner relationships, including knowledge transfer from external partners during the initial build.
Report platform status, risks and metrics to AI program leadership.