Senior AI Engineer

Ultimus Fund Solutions is hiring a Senior AI Engineer to help operationalize enterprise AI models across the full technical lifecycle. This remote role sits at the intersection of machine learning engineering and production systems, partnering closely with AI Data Scientists and AI Developers to turn model work into reliable, governed capabilities.

In this position, you will design and scale the pipelines and infrastructure that support automated workflows, integrate AI into existing financial platforms, and establish MLOps practices with clear technical KPIs. The focus is on execution quality, measurable outcomes, and dependable performance in production environments.

What you’ll do

• Architect and scale machine learning pipelines that enable automated workflows across Fund Accounting, Transfer Agency, and Onboarding
• Oversee development and deployment of robust AI infrastructure using enterprise data lakes and cloud platforms
• Lead technical initiatives to integrate AI capabilities into existing legacy systems and financial platforms
• Establish MLOps best practices and define technical KPIs tied to system uptime, model latency, and infrastructure efficiency
• Mentor junior engineering staff and advise the Managing Director on technical priorities, including securing AI governance

What you bring

• 7+ years of experience across software engineering, data engineering, or machine learning operations
• Proven ability to architect scalable data pipelines and deliver measurable technical outcomes
• Deep expertise in Python, SQL, and enterprise cloud data platforms
• Ability to work with business operations to translate operational needs into technical architecture
• Financial services or fund administration experience is preferred, but not required
• Strong technical leadership and mentoring skills
• An operator mindset focused on execution and reliable technical results

Key technologies

• Python
• SQL
• Enterprise data lakes
• Cloud platforms

Position summary

The Senior AI Engineer will own the end-to-end technical lifecycle of enterprise AI models, from data pipeline architecture to deployment and monitoring. Working with AI Data Scientists and AI Developers, the role operationalizes models, supports robust data governance, and drives measurable outcomes such as improved system scalability and reduced latency. This is a hands-on leadership role that balances complex engineering demands with practical business application and aligns technical direction across the AI department.