Senior Architect - AI Infrastructure Platform Services

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 

Job Description:
This job is responsible for defining an architectural vision and solution that supports the strategic outcomes of the Business' Products and Services. Key responsibilities include defining the target operating environment, designing for client resiliency, assisting with solution design, and defining non-functional requirements. Job expectations include working with stakeholders and service providers aligned to the Business' strategic objectives, evaluating the impact of strategic design decisions, and contributing to the architecture roadmap.

Position Summary:

Architect and Engineer Highly Performant AI Infrastructure Platform Services for Model Development and Deployment/Inference platform and associated services with deep understanding of regulated finance environments.

Responsibilities:

• Works across the business, operations and technology to create the solution intent and architectural vision for complex solutions and prioritize functional and non-functional requirements into a technology backlog to enable the technology roadmap and functionality to support evolving capabilities and services
• Contributes to the creation of the architecture roadmap of defined domains (Business, Application, Data, and Technology) in support of the product roadmap and the development of best practices including standardized templates
• Clarifies the architecture, assists with system design to support implementation, and provides solution options to resolve any architectural impediments
• Facilitates solution driven discussions, leads the design of complex architectures, and finds creative solutions through knowledge of domain, practical experiments, and proof of concepts while ensuring architecture is flexible, modular, and adaptable
• Educates team members on the technology practices, standardization strategies, and best practices to create innovative solutions
• Supports the team as needed to select the technology stack required for solutions and helps select preferred technology products
• Performs design and code reviews to ensure all non-functional requirements are sufficiently met (for example, security, performance, maintainability, scalability, usability, and reliability)
• Manage and lead design and development of high-performance framework for Jupyter Workbench and Inferencing Engines like Triton and VLLM
• Work closely with the Data Science teams to access their needs of new tooling for their workbench and develop those solutions.
• Collaborating with data scientists, engineers, and application developers to build, design, develop, optimize and deploy machine learning models with MLOps guidelines and streamline ML Lifecycle
• Develop and maintain performance benchmarks and metrics using tools – Prometheus, Thanos and Grafana.
• Automate machine learning pipelines, including data preprocessing, feature engineering, and model training.
• Develop and optimize distributed AI systems for high-performance computing
• Implement microservices architectures to support modular and maintainable AI solutions
• Design, implement, and maintain LLMOps pipelines and workflows to streamline the model deployment lifecycle
• Develop and maintain technical documentation and knowledge base articles to share best practices and lessons learned with the Tech Infrastructure Team.

Required Qualifications:

• 10+ Years Experience in Information Technology with emphasis of working in regulated environments
• Proficient in NVIDIA tech stack, leveraging GPUs for accelerated AI workloads using CUDA stack
• Skilled in Python for data science, machine learning, and AI development Python, including core data science libraries NumPy, scikit-learn etc.
• Working level knowledge