BNY · 3 days ago
Public Cloud Operations, Vice President, Production Services Infrastructure Support
Pittsburgh, PA
Full-time
Onsite
Mid, Senior Level
5+ years expBNY is a leading global financial services company at the heart of the global financial system, influencing nearly 20% of the world’s investible assets. The role of Vice President, Production Services Infrastructure Support focuses on operationalizing and securing the adoption of Google Cloud Platform and Azure, while supporting critical AI infrastructure and ensuring compliance and security across multi-cloud environments.
Financial Services
Responsibilities
Operationalize and secure BNY’s adoption of Google Cloud Platform (GCP) and Azure from Microsoft
Scale GCP and Azure AI services usage securely and efficiently across the enterprise, enabling innovation while maintaining control and compliance
Support critical AI infrastructure (Eliza) and services for sustaining ModelOps governance, monitoring, automation, scaling and capacity management
Support IAM using B2C capabilities across multi cloud service providers (Azure, GCP, OCI) during the following APAC, EMEA, and US time zones
Implement critical Run-the-Bank (RTB) and new projects include: Eliza, Eliza AI Hub, Eliza Brain (GCP Google brain), and Eliza as a Service (EaaS)
Champion key operational requirements: Model Lifecycle Management, Monitoring & Performance, Data Management, Governance & Compliance, Security & Access Control, Reliability & Scalability, Automation & Optimization, Collaboration & Knowledge Sharing, Continuous Improvement
Maintain secure, reliable data pipelines for model training and inference
Ensure data quality checks (validity, completeness, freshness) before retraining
Track data lineage and provenance to support audits and compliance
Apply data governance frameworks across multi-cloud environments
Document models for auditability and transparency
Enforce responsible AI principles (fairness, explainability, bias mitigation)
Ensure compliance with regulations (GDPR, HIPAA, SOC 2, industry-specific rules)
Maintain approval workflows for promoting models into production
Control access to model APIs and training datasets (least-privilege IAM)
Protect sensitive data with encryption at rest and in transit
Monitor and prevent adversarial attacks or misuse of AI models
Conduct regular security reviews of deployed models and APIs
Implement autoscaling of inference services based on demand
Design for high availability and disaster recovery across regions/clouds
Perform load testing for AI services under peak conditions
Use A/B testing and canary releases for safe rollouts of new model versions
Automate retraining pipelines based on triggers (new data, performance thresholds)
Optimize infrastructure usage (e.g., GPU/TPU scheduling, spot instances)
Apply FinOps practices to control costs of training and inference
Leverage AI Ops for predictive maintenance of AI services
Provide documentation, runbooks, and knowledge bases for model operations
Collaborate with Data Science, DevOps, and Compliance teams
Educate stakeholders on model behaviors, risks, and limitations
Conduct postmortems for model failures or degraded performance
Benchmark models and platforms across Azure, Google Cloud, and hybrid environments
Incorporate new MLOps/ModelOps tooling for efficiency and compliance
Establish feedback loops from business outcomes back into model evaluation
Regularly reassess KPIs and SLOs to align with evolving business needs
Qualification
Required
Bachelor's degree in computer science, Information Technology, or a related field
Typically, 5-10 years of related infrastructure experience required; experience in the securities or financial services industry is a plus
Maintain secure, reliable data pipelines for model training and inference
Ensure data quality checks (validity, completeness, freshness) before retraining
Track data lineage and provenance to support audits and compliance
Apply data governance frameworks across multi-cloud environments
Document models for auditability and transparency
Enforce responsible AI principles (fairness, explainability, bias mitigation)
Ensure compliance with regulations (GDPR, HIPAA, SOC 2, industry-specific rules)
Maintain approval workflows for promoting models into production
Control access to model APIs and training datasets (least-privilege IAM)
Protect sensitive data with encryption at rest and in transit
Monitor and prevent adversarial attacks or misuse of AI models
Conduct regular security reviews of deployed models and APIs
Implement autoscaling of inference services based on demand
Design for high availability and disaster recovery across regions/clouds
Perform load testing for AI services under peak conditions
Use A/B testing and canary releases for safe rollouts of new model versions
Automate retraining pipelines based on triggers (new data, performance thresholds)
Optimize infrastructure usage (e.g., GPU/TPU scheduling, spot instances)
Apply FinOps practices to control costs of training and inference
Leverage AI Ops for predictive maintenance of AI services
Provide documentation, runbooks, and knowledge bases for model operations
Collaborate with Data Science, DevOps, and Compliance teams
Educate stakeholders on model behaviors, risks, and limitations
Conduct postmortems for model failures or degraded performance
Benchmark models and platforms across Azure, Google Cloud, and hybrid environments
Incorporate new MLOps/ModelOps tooling for efficiency and compliance
Establish feedback loops from business outcomes back into model evaluation
Regularly reassess KPIs and SLOs to align with evolving business needs
Preferred
Professional certifications in relevant technologies or infrastructure management are preferred
Benefits
Highly competitive compensation
Benefits
Wellbeing programs
Generous paid leaves
Paid volunteer time
Company
BNY
We help make money work for the world — managing it, moving it and keeping it safe.
10001+ employees
Funding
Current Stage
Late StageLeadership Team
Brian A. Ruane
CEO Government Securities Services & Global Client Management
Chris Kearns
CEO, Depositary Receipts
Recent News
PR Newswire
2024-11-01
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