招聘

Public Cloud Operations, Vice President, Production Services Infrastructure Support
Pittsburgh, PA, United States; Lake Mary, FL, United States
·
On-site
·
Full-time
·
1mo ago
必备技能
GCP
Azure
Public Cloud Operations – VP, Production Services Infrastructure Support
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #Life AtBNY is all about. Join us and be part of something extraordinary.
We’re seeking a future team member for the role of Public Cloud Operations – VP, Production Services Infrastructure Support to join our Technology Services Group (TSG) team. This role is located in Pittsburgh, PA or Lake Mary, FL.
In this role, you’ll make an impact in the following ways:
· 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 Model Ops 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."
To be successful in this role, we’re seeking the following:
Data Management
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Maintain secure, reliable data pipelines for model training and inference.
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Ensure data quality checks (validity, completeness, freshness) before retraining.
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Track data lineage and provenance to support audits and compliance.
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Apply data governance frameworks across multi-cloud environments.
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Bachelor’s degree in computer science, Information Technology, or a related field. Professional certifications in relevant technologies or infrastructure management are preferred.
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Typically, 5-10 years of related infrastructure experience required; experience in the securities or financial services industry is a plus
Governance & Compliance:
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Document models for auditability and transparency.
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Enforce responsible AI principles (fairness, explainability, bias mitigation).
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Ensure compliance with regulations (GDPR, HIPAA, SOC 2, industry-specific rules).
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Maintain approval workflows for promoting models into production.
Security & Access Control:
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Control access to model APIs and training datasets (least-privilege IAM).
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Protect sensitive data with encryption at rest and in transit.
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Monitor and prevent adversarial attacks or misuse of AI models.
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Conduct regular security reviews of deployed models and APIs.
Reliability & Scalability:
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Implement autoscaling of inference services based on demand.
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Design for high availability and disaster recovery across regions/clouds.
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Perform load testing for AI services under peak conditions.
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Use A/B testing and canary releases for safe rollouts of new model versions.
Automation & Optimization:
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Automate retraining pipelines based on triggers (new data, performance thresholds).
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Optimize infrastructure usage (e.g., GPU/TPU scheduling, spot instances).
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Apply Fin Ops practices to control costs of training and inference.
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Leverage AI Ops for predictive maintenance of AI services.
Collaboration & Knowledge Sharing:
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Provide documentation, runbooks, and knowledge bases for model operations.
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Collaborate with Data Science, DevOps, and Compliance teams.
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Educate stakeholders on model behaviors, risks, and limitations.
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Conduct postmortems for model failures or degraded performance.
Continuous Improvement
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Benchmark models and platforms across Azure, Google Cloud, and hybrid environments.
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Incorporate new MLOps/Model Ops tooling for efficiency and compliance.
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Establish feedback loops from business outcomes back into model evaluation.
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Regularly reassess KPIs and SLOs to align with evolving business needs.
At BNY, our culture speaks for itself, check out the latest BNY news at: BNY Newsroom BNY LinkedIn
Here’s a few of our recent awards:
· America’s Most Innovative Companies, Fortune, 2025
· World’s Most Admired Companies, Fortune 2025
· “Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
- BNY is an Equal Employment Opportunity/Affirmative Action Employer
- Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans
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关于BNY Mellon

BNY Mellon
PublicBNY Mellon is a global investment company and one of the world's oldest banks, providing investment management and investment services to institutions, corporations and high-net-worth individuals. The company serves as a custodian for assets and provides treasury services, fund administration and other financial services.
10,001+
员工数
New York City
总部位置
$40B
企业估值
评价
4.0
31条评价
工作生活平衡
3.4
薪酬
4.8
企业文化
3.9
职业发展
4.1
管理层
3.5
78%
推荐给朋友
优点
Prestigious brand and networking opportunities
Excellent compensation and bonus structure
Exposure to complex financial systems
缺点
Work-life balance can be difficult
Legacy technology in some areas
High-pressure environment with strict deadlines
薪资范围
28个数据点
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Junior/L3 · Associate Client Reporting Performance I
1份报告
$70,635
年薪总额
基本工资
$61,422
股票
-
奖金
-
$70,635
$70,635
面试经验
8次面试
难度
3.0
/ 5
时长
21-35周
体验
正面 0%
中性 75%
负面 25%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
HR/Recruiter Screen
4
Technical Interview
5
Behavioral Interview
6
Final Round/Superday
常见问题
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
Past Experience
Culture Fit
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