7+ years of experience in software engineering, data engineering, or machine learning operations
Proven ability to architect scalable data pipelines with measurable outcomes
Expertise in Python, SQL, and enterprise cloud data platforms
Skilled in translating business operations needs into technical architecture
Experience in financial services or fund administration is a plus
Strong leadership and mentoring capabilities
Execution-focused with an operator mindset
Responsibilities
Architect and scale machine learning pipelines for automated workflows
Oversee development and deployment of AI infrastructure using data lakes and cloud platforms
Lead initiatives to integrate AI into legacy systems and financial platforms
Establish MLOps best practices and technical KPIs for system performance
Mentor junior engineers and advise on technical priorities and AI governance
Benefits
Collaborative work environment with cross-functional teams
Opportunities for professional development and mentorship
Access to cutting-edge AI technologies and tools
Impactful role in shaping AI strategy within the organization
Potential for career advancement in a growing field
Full Job Description
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. The role will partner with AI Data Scientists and AI Developers to operationalize models, ensure robust data governance, and deliver measurable technical outcomes including improved system scalability and reduced latency. The role requires a hands-on technical leader who can balance complex engineering with practical business application and drive technical alignment across the AI department.
Key Responsibilities
Architect and scale machine learning pipelines to support automated workflows across Fund Accounting, Transfer Agency, and Onboarding
Oversee the development and deployment of robust AI infrastructure leveraging 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 technical KPIs tied to system uptime, model latency, and infrastructure efficiency
Mentor junior engineering staff and advise the Managing Director on technical priorities and secure AI governance
Qualifications
7+ years of experience across software engineering, data engineering, or machine learning operations
Demonstrated ability to architect scalable data pipelines and deliver measurable technical outcomes
Deep expertise in Python, SQL, and enterprise cloud data platforms
Ability to work effectively with business operations to translate operational needs into technical architecture
Experience in financial services or fund administration preferred but not required
Strong technical leadership and mentoring skills
Operator mindset with a focus on execution and reliable technical outcomes
