Senior Architect - AI

Bank of America•Pennington, AL

1d•$140,500 - $205,000•Onsite

About The Position

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. This role serves as a senior AI architecture leader responsible for defining enterprise patterns, standards, and decision frameworks that guide the adoption of AI across Global Technology. The role provides architectural leadership spanning AI platforms, agentic systems, retrieval architectures, model integration, workflow automation, and enterprise AI governance. Working closely with CIO architecture teams, platform engineering, security, and risk partners, this role helps translate rapidly evolving AI capabilities into practical, scalable, and governed enterprise solutions. As the bank expands AI adoption across Consumer, Wealth, Business Banking, and Markets, a consistent architecture approach is critical to maximizing business value while managing risk and complexity. This role helps ensure AI investments are built on reusable foundations, aligned to enterprise standards, and integrated effectively with data, applications, and business processes. The outcome is accelerated solution delivery, improved productivity, stronger governance, and a scalable AI ecosystem that can support current and future business needs.

Requirements

15+ years in enterprise architecture, solution architecture, software engineering, or distributed systems design
8+ years of experience architecting AI/ML, NLP, or advanced analytics solutions.
2+ years of experience designing enterprise GenAI, RAG, and agentic AI solutions.
Strong knowledge of AI/ML concepts including LLMs, RAG, embeddings, vector databases, evaluation frameworks, and agent-based architectures
Experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI services, Azure OpenAI, or equivalent technologies
Familiarity with AI orchestration frameworks, workflow automation, and enterprise integration patterns
Understanding of security, governance, privacy, and risk considerations for AI solutions
Proven ability to influence senior stakeholders and drive architecture decisions in regulated environments
Strong communication skills with the ability to simplify complex AI concepts and drive alignment across technical and business audiences

Nice To Haves

Experience with agentic AI, multi-agent systems, MCP, and emerging AI interoperability standards
Experience with Microsoft AI ecosystem capabilities including Copilot Studio, Azure AI Foundry, Azure OpenAI, and GitHub Copilot
Experience with AWS AI services including Amazon Bedrock, SageMaker, and AI application architectures
Knowledge of knowledge graphs, semantic search, vector databases, and enterprise retrieval architectures
Experience defining AI governance, model lifecycle management, and responsible AI practices
Experience operating in large-scale, highly regulated enterprise 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)
Define enterprise AI architecture strategy, standards, governance models, and decision frameworks for AI solutions and platforms.
Establish reusable architecture patterns, reference architectures, templates, and guardrails to drive consistency and responsible AI adoption.
Design and govern enterprise AI agents, multi-agent systems, orchestration models, workflow automation, and human-in-the-loop controls.
Guide AI platform, model, and solution architecture decisions across Microsoft Copilot Studio, Azure AI, Orchestra, and emerging AI capabilities.
Define patterns for RAG, vector databases, semantic retrieval, enterprise knowledge architectures, and AI-ready data access.
Establish standards for model integration, evaluation, observability, lifecycle management, explainability, and trustworthiness.
Define integration architectures across APIs, events, MCP, AI platforms, and agent-to-agent communication frameworks.
Embed security, risk, compliance, identity, access management, data protection, and policy enforcement into AI architecture designs.
Evaluate trade-offs across scalability, resilience, governance, security, performance, and business value while ensuring alignment with enterprise standards.
Lead enterprise AI adoption through stakeholder engagement, visual communication, architect enablement, mentoring, and long-term AI strategy development