Head of AI Infrastructure & Machine Learning Operations

Apex Group • Boston, MA

4d • Onsite

About The Position

The Apex Group was established in Bermuda in 2003 and is now one of the world’s largest fund administration and middle office solutions providers. Our business is unique in its ability to reach globally, service locally and provide cross-jurisdictional services. With our clients at the heart of everything we do, our hard-working team has successfully delivered on an unprecedented growth and transformation journey, and we are now represented by over circa 13,000 employees across 112 offices worldwide.Your career with us should reflect your energy and passion. That’s why, at Apex Group, we will do more than simply ‘empower’ you. We will work to supercharge your unique skills and experience. Take the lead and we’ll give you the support you need to be at the top of your game. And we offer you the freedom to be a positive disrupter and turn big ideas into bold, industry-changing realities. For our business, for clients, and for you Head of AI Infrastructure & Machine Learning Ops Role Location Greater Boston Area Reports To Chief AI and Data Science Officer We are seeking an ambitious and visionary Head of AI Infrastructure & Machine Learning Ops to join our leadership team and play a critical role in scaling the infrastructure, tooling, and deployment capabilities for AI and ML systems across the Apex Group. Reporting directly to the Chief AI and Data Science Officer, this is a senior strategic appointment with global scope. The successful candidate will be responsible for building secure, scalable, and compliant platforms to accelerate AI innovation and ensure operational excellence in a highly regulated financial services environment.

Requirements

• Proven leadership in designing scalable, cloud-native or hybrid AI/ML platforms that support experimentation and secure enterprise deployment.
• Deep expertise in MLOps strategy and execution, including end-to-end pipelines, CI/CD, model versioning, and retraining workflows.
• Hands-on experience with model deployment and runtime management across varied environments (batch, real-time, REST, edge), using tools like MLflow, SageMaker, Databricks, or other equivalent.
• Strong background in monitoring, observability, and incident response — including drift detection, fairness tracking, latency alerts, and recovery protocols.
• Skilled in building secure, compliant AI infrastructure aligned with regulatory standards (e.g., GDPR, EU AI Act).

Nice To Haves

• Strategic thinker with strong operational and technical execution capabilities.
• Passionate about responsible AI, platform resilience, and infrastructure innovation.
• Comfortable working in high-ambiguity, fast-paced startup-like environments.
• Collaborative leader with strong interpersonal and communication skills.
• High integrity, accountability, and a commitment to ethical technology adoption.

Responsibilities

• Establish a scalable AI runtime environment to support rapid prototyping and early deployment of LLM agents and agentic workflows.
• Design and implement a robust MLOps stack with model versioning, CI/CD pipelines, and automated monitoring for operational resilience.
• Build secure, compliant AI development and deployment architectures while aligning with AI governance framework.
• Collaborate cross-functionally to ensure infrastructure meets the evolving needs.

Benefits

• Be part of a dynamic and fast-paced team that makes a genuine impact on the success of the entire organisation.
• Opportunity to work with a diverse, agile, and global team.
• Exposure to all aspects of the business, cross-jurisdiction.
• A genuinely unique opportunity to be part of an expanding large global business.
• Competitive remuneration in line with skills and experience.
• Training and development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed