Director of Software Engineering (MLOps & ML Governance)

PanAgora Asset Management is focused on transforming financial lives and fostering a flexible work environment. The Director of Software Engineering will lead the MLOps function and ensure scalable, secure, and compliant machine learning solutions while collaborating with various teams to achieve strategic business initiatives.

Responsibilities:

• Leads the execution of deliverables with the risk and engineering teams ensuring projects are completed on time and within predefined requirements and budgets
• Accountable for team performance within assigned projects, including software engineering and MLOps initiatives
• Serves as subject matter expert on multiplatform applications and ML infrastructure, determining course of action under the direction of systems leadership
• Directs the system development lifecycle including the design, coding, testing, documentation, maintenance, and support of proprietary and purchased software systems and applications
• Leads the design, implementation, and scaling of enterprise MLOps platforms and capabilities, including CI/CD pipelines for ML, model versioning, automated testing, monitoring, and model lifecycle management
• Establishes best practices for model deployment, observability, performance monitoring, drift detection, and retraining strategies
• Partners with Data Science, Risk, Compliance, Legal, and Information Security teams to ensure machine learning systems meet regulatory, governance, and risk management requirements
• Implements and oversees ML governance frameworks including model documentation, validation, explainability, auditability, fairness/bias monitoring, and model risk management controls
• Ensures adherence to enterprise data governance, privacy, and AI risk policies, including responsible AI standards
• Recommends innovation and improvements to policy or procedures; has the latitude to make decisions affecting mid- to long-term operational results
• Develops long- and short-term business and technology strategies aligned to AI/ML roadmaps
• Responsible for managing operating costs and budgets, including infrastructure investments for ML platforms. Makes decisions on pay, performance, appraisals, schedules, discipline, and hiring
• Builds and leads a high-performing MLOps and engineering organization, establishing clear career paths and leadership development for managers and senior engineers

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field; or equivalent combination of professional experience and/or training required
• 10+ years of experience in software engineering, including experience building distributed or cloud-based systems
• 4+ years successfully managing teams (including managers), with demonstrated ability to develop, motivate, and direct leaders and technical contributors
• Proven experience leading or building an MLOps function or production-grade ML platforms in an enterprise environment
• Strong understanding of ML lifecycle management including model training, validation, deployment, monitoring, and governance
• Experience implementing ML governance and model risk management frameworks (e.g., documentation standards, validation controls, bias/fairness testing, explainability techniques, audit readiness)
• Familiarity with regulatory expectations for AI/ML in highly regulated industries (e.g., financial services, healthcare, etc., as applicable)
• Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code
• Strong understanding of data governance, privacy, security, and compliance considerations related to AI/ML systems
• Ability to manage a leadership pipeline by mentoring subordinate managers and nurturing senior technical talent
• Excellent executive communication skills with the ability to translate complex ML and risk topics into business-aligned decisions