Senior Engineer- Agentic AI

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 and leading the engineering approach for complex features to deliver significant business outcomes. Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in a number of techni [... source excerpt omitted ...] s accountable for end-to-end solution design and delivery. Position Summary: We’re seeking a Senior Engineer to lead the design and implementation of Agentic AI across the SDLC. You will define the strategy, architecture, and operating model for applying GitHub Copilot, Microsoft Copilot Studio, Azure AI Foundry, and the Microsoft Agentic Framework—enhanced by RAG, context engineering, prompt engineering, and knowledge graphs—to automate and elevate developer workflows from planning through production. You will partner with product, platform, risk, and delivery teams to drive measurable outcomes, ensure responsible use, and scale adoption across the enterprise. Responsibilitie [... source excerpt omitted ...] e reference architectures and guardrails for Copilot‑based coding, testing, and automation. Engineering & Delivery: - Lead delivery of AI agents that automate SDLC tasks such as requirements analysis, design reviews, test generation, traceability, code‑quality enforcement, documentation updates, and release readiness. - Build Copilots with Copilot Studio, integrating plugins, enterprise search, and workflow actions, and operationalize models in Azure AI Foundry with full lifecycle support for evaluation, monitoring, safety, and CI/CD/CT pipelines for prompts and agents. Data, RAG, and Knowledge Graphs: - Define ontology and schema for domain knowledge graphs and integrate code m