Software Engineer III-Generative AI Platform Engineering

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 and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

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

Position Summary :

This is a hands-on software engineering role focused on building enterprise-grade Generative AI, Data Science, and AI Platform capabilities within Bank of America's strategic AI ecosystem. The engineer will work as an individual contributor responsible for designing, developing, and delivering reusable GenAI platform services, frameworks, APIs, and application components that support AI model development, deployment, inferencing, automation, and governance.

The successful candidate will partner with senior engineers, architects, product owners, and data scientists to develop scalable, secure, and resilient solutions leveraging modern AI frameworks, cloud-native technologies, distributed computing platforms, and enterprise engineering practices.

This role is ideal for an engineer passionate about Generative AI, application development, platform engineering, automation, and building reusable capabilities that accelerate enterprise AI adoption.

This job is responsible for developing and delivering complex requirements to accomplish business goals. Key responsibilities of the job include ensuring that software is developed to meet functional, non-functional and compliance requirements, and solutions are well designed with maintainability/ease of integration and testing built-in from the outset. Job expectations include a strong knowledge of development and testing practices common to the industry and design and architectural patterns.

Responsibilities:

• Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
• Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
• Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
• Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
• Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
• Automates manual release activities
• Designs, develops, and maintains automated test suites (integration, regression, performance)
• Develop and enhance enterprise Generative AI platform capabilities, reusable services, and self-service tools.
• Design and build AI-powered applications, agentic workflows, RAG solutions, and MCP-enabled services.
• Develop scalable APIs, microservices, and platform components supporting AI/ML lifecycle management.
• Build and maintain frameworks supporting model development, fine-tuning, deployment, inferencing, monitoring, and observability.
• Implement event-driven and streaming solutions leveraging technologies such as Kafka and distributed processing platforms.
• Contribute to CI/CD pipelines, automation frameworks, testing strategies, and DevOps practices.
• Collaborate with platform engineers, architects, data scientists, and business stakeholders to deliver new capabilities.
• Participate in design discussions, code reviews, sprint planning, story refinement, and estimation activities.
• Ensure solutions meet enterprise standards for