Core Responsibilities

　　1. Assesses business requirements and the architectural framework of Artificial Intelligence/Machine Learning solutions to meet business needs, with internal and external clients and partners.

　　2. Builds the deployment plan for highly scalable and secure Artificial Intelligence platforms, applications, and systems that run in various cloud infrastructures and Artificial Intelligence devices successfully.

　　3. Applies architecture specification and documents technical and configuration for all users (customers, engineering teams, product teams); resolves Artificial Intelligence/Machine Learning solution deployment issues.

　　4. Builds relationships with trusted advisory stakeholder relationships, and acts as a SME for Artificial Intelligence/Machine Learning related products and services in specific verticals; staying current on the latest Artificial Intelligence/Machine Learning technologies and tools.

　　5. Applies moderately complex machine learning algorithms and technologies into organizational practices, such as regression models.

　　6. Analyzes the statistical analyses on business and processes using machine learning techniques to find out opportunities for business development and process improvement.

　　7. Performs the A/B testing tasks and initiatives on statistical models, machine learning algorithms and systems.

　　8. Optimizes statistical models continuously to achieve best performance of machine learning algorithms.

　　9. Validates business problems and needs; ensures appropriate AI technologies and tools are utilized to solve problems.

　　10. Pilots AI models and prototype applications; evaluates whether business challenges are addressed.

　　11. Performs code reviews, optimizes algorithms and models and conducts experiments to ensure the functionality and performance of AI products or solutions.

　　12. Participates in special projects and performs other duties as assigned.

　　13. Participates in special projects and performs other duties as assigned.

　　Qualifications

　　1. Minimum of eight years related work experience, with at least three years of technology architect experience.

　　2. Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

　　3. Broad knowledge of the financial services industry and analytics ecosystem.

　　4. Hands-on experience in one or more IT platforms, development tools and programming language:Experience and expertise in products using modern analytics cloud-based services and platforms such as AWS Sagemaker, Glue ETL, EMR, Data Wrangler, Glue Catalog, S3, Python, Tableau, Pyspark, SQL, Attunity and other adjacent tools used for data exploration such as AWS Athena and Presto.Experience with Continuous Integration, Continuous Deployment, DevOps, and Infrastructure as code utilizing tools such as Atlassian Bamboo, Github Actions, AWS Cloud Formation, pytest, Cucumber, Splunk, AWS Cloudwatch and other testing and monitoring tools.Understanding of DDD and data fabric concepts; Experience implementing tools like Dremio.Experience architecting ML Development Platforms (AWS Sagemaker and associated services)Experience architecting ML Ops and Automated controls (Automated model deployment-CI/CD, Automated Model Governance, Model Feature Management)Experience architecting GenAI and LLM model services and use cases (ChatGPT,Azure OpenAI, Google Bard, AWS Bedrock, CodeWhisperer, GitHub Copilot, etc)5. Expert knowledge of the following technical lead practices and concepts:Full product life cycleIT vendor product assessmentArchitecture design patternsWide range of cloud and emerging technologies within technical specialtyPerformance and stress testing; resiliency and highly availabilitySecurity architecture and cost optimization techniquesQuality assurance methodology and InspectionsTechnical standards and deliverablesMigration and integrationEstimating, including design, development/purchase, and installationProduction acceptance (including elevations), data modeling, data sharing, reusable components, and related advanced development practices.Special Factors

　　Sponsorship

　　Vanguard is not offering visa sponsorship for this position.

　　About Vanguard

　　We are Vanguard. Together, we're changing the way the world invests.

　　For us, investing doesn't just end in value. It starts with values. Because when you invest with courage, when you invest with clarity, and when you invest with care, you can get so much more in return. We invest with purpose - and that's how we've become a global market leader. Here, we grow by doing the right thing for the people we serve. And so can you.

　　We want to make success accessible to everyone. This is our opportunity. Let's make it count.

　　Inclusion Statement

　　Vanguard's continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: "Do the right thing."

　　We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard's core purpose through our values.

　　When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose.

　　Our core purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

　　How We Work

　　Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.