Director, AI / Machine Learning Software Engineer
BNY Mellon1 day ago
Responsibilities
- Define and lead the AI Ops strategy, standards, frameworks, and best practices for deploying, monitoring, governing, and supporting AI/ML solutions in production.
- Drive automation for AI/ML pipelines, model deployment, monitoring, alerting, and incident-response processes.
- Build observability frameworks covering model performance, data health, system reliability, and operational risks.
- Establish operational controls and governance processes for AI applications, models, and data pipelines.
- Improve production reliability, scalability, resiliency, and efficiency for AI-powered applications and platforms.
- Influence architecture decisions and cross-functional technical strategy for secure, compliant, and operationally excellent AI solutions.
- Lead continuous improvement through incident reviews, root-cause analysis, and adoption of lessons learned.
- Mentor senior engineers and technical teams in AI Ops, SRE, and production-support best practices.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related technical field; an advanced degree is preferred.
- Significant experience in software engineering, machine learning engineering, AI/ML operations, or site reliability engineering.
- Proven experience leading enterprise-scale AI/ML production operations in a highly regulated environment.
- Strong expertise in cloud platforms, distributed systems, automation, CI/CD, and infrastructure as code.
- Experience with observability, monitoring, logging, and alerting frameworks for complex production environments.
- Deep understanding of AI/ML lifecycle management, including model deployment, monitoring, governance, and retraining.
- Strong knowledge of production support, incident management, resiliency engineering, and operational controls.
- Ability to influence senior stakeholders, architecture decisions, and cross-functional technical strategy.
- Excellent communication and leadership skills, including the ability to bridge engineering and production teams.
- Experience in financial services or another highly regulated industry is preferred.
- Familiarity with governance, risk, and compliance considerations for AI/ML applications is preferred.
- Experience supporting agentic AI solutions, modern ML platforms, and large-scale data pipelines is preferred.
- Knowledge of security, reliability, and performance engineering best practices for AI platforms is preferred.
Benefits
- Opportunity to shape the AI operational backbone for Investments & Wealth and influence enterprise-wide standards for bringing AI solutions into production, managing them, and scaling them.
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About BNY Mellon
BNY Mellon is a public, New York–based global financial services company providing investment and wealth management, asset servicing, clearance, collateral, and treasury services to institutions, banks, governments, and individuals. It also offers data and investment operations software, including the Eagle platform, delivered as cloud and managed services. Founded in 1784, it is one of the world’s largest custodian banks and asset servicers.