Domain Architect- Analytics and AI\/ML, Senior Specialist

Are you passionate about Analytics and AI/ML architecture? Are you interested in defining architectural solutions leveraging cloud-based technologies? This is an exciting opportunity for you to be part of Chief Data and Analytics Office (CDAO) and you will be working with amazing talented architects in achieving Data and Analytics outcomes.

CDAO as a subdivision under IT, we're responsible for transforming how crew use data so clients and investors can thrive. Our mission is to accelerate Vanguard's flywheel by using data to inform and elevate every decision. We power information through data - improving outcomes, guiding strategies, and changing behavior.

CDAO is looking for a Senior Domain Architect who is motivated and ready to strategize and architect Analytics and AI/ML solutions. This role will provide expert level IT architecture and technical lead services, including the direction, evaluation, selection, configuration, implementation, and integration of new and existing technologies. Drives the implementation of Artificial Intelligence and Machine Learning architecture, utilizing approaches of various Artificial Intelligence and Machine Learning technologies and methods to address client' business problems and needs, while complying with company's strategies and business goals.

Leads the definition of technology roadmaps and architecture for a product family according to business strategies and enterprise architecture framework, while working closely with the product teams and product owners. As a Senior Domain Architect, you are expected to play key role in shaping technology architecture strategy and direction for following areas,

- Analytics Platforms (Data Visualization, Reporting, Ingestion, Transformation, Prep, Query)

- MDLC (ML Dev, ML Ops, ML Governance)

- GenAI and LLM model use case enablement

The Domain Architect owns the architectural decisions for the team and this role is the visionary force behind the technical solutions for business problems.

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 cycle
• IT vendor product assessment
• Architecture design patterns
• Wide range of cloud and emerging technologies within technical specialty
• Performance and stress testing; resiliency and highly availability
• Security architecture and cost optimization techniques
• Quality assurance methodology and Inspections
• Technical standards and deliverables
• Migration and integration
• Estimating, including design, development/purchase, and installation
• Production 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.