Principal Engineer

Bank of America•Charlotte, NC

9d•Onsite

About The Position

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 solutions at the program or portfolio level, to deliver significant business outcomes. Key responsibilities include continuously improving the design, quality, and reuse of the solution and delivering technology enablers that improve development efficiencies for the solution. Job expectations include familiarity with at least one area of engineering, acting as a “go to” reference across the organization, and applying knowledge to improve technical competencies through recruitment and development activities. We are seeking a Principal Engineer to lead the transformation of Erica, our AI-powered virtual assistant, from an early-generation AI system to a next-generation AI stack leveraging Generative AI and cloud technologies. This role is critical in shaping the future of conversational AI at Bank of America, ensuring scalability, reliability, and innovation. The ideal candidate will have a strong engineering background and will be passionate about building cutting-edge AI platforms that deliver exceptional customer experiences.

Requirements

8+ years of experience in software engineering/IT.
Proven experience in AI/ML, Generative AI, and cloud-based architectures.
Expertise in Python and/or Java, including object-oriented design and REST API development.
Strong knowledge of microservices architecture, distributed systems, and data processing (structured and unstructured datasets).
Familiarity with machine learning frameworks, LLMs, and agentic AI solutions.

Nice To Haves

Experience with financial services or large-scale enterprise platforms.
Hands-on experience with cloud platforms (AWS, Azure, GCP).

Responsibilities

Develops the engineering approach for the entire program/portfolio solution and works with Architecture, to develop/analyze/deliver the implementation of technical enablers
Leads the planning, definition, and design of the complex features which span multiple teams and explore solution alternatives
Creates ideas on designing complex technology and solution development approaches
Leads the technical oversight for teams in solution development including design reviews and code within own domain
Defines the technology tool stack for the solution within ranged of internally approved and supported technologies
Explores state-of-the-art technologies to improve development efficiencies, quality of test/QA coverage, and release management
Leads and is responsible for the end-to-end test strategy/creation/adherence, and the integration between teams for a program/portfolio solution
Define and lead the engineering approach for the next-generation Erica AI platform.
Collaborate with architecture teams to design and implement technical enablers for Generative AI and cloud integration.
Drive planning, definition, and design of complex features spanning multiple teams.
Provide technical oversight, including design reviews and code quality assurance.
Explore and integrate state-of-the-art technologies to improve development efficiency and platform performance.
Develop architectural approaches for AI software and hardware integration, focusing on scalability and agent-based solutions.
Partner with business stakeholders to align technology strategy with organizational goals.
Ensure compliance with security, risk management, and regulatory standards.