Software Engineer III – Generative AI Platform Engineering

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.

• 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 Dev Ops 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 security, scalability, governance, resiliency, and operational excellence.
• Support platform observability, monitoring, and performance optimization initiatives.
• Continuously evaluate emerging AI technologies and contribute innovative solutions to enhance platform capabilities.

• Develop code and automated tests to deliver stories and requirements meeting quality and compliance standards.
• Participate in application design leveraging data, application, integration, and platform architecture patterns.
• Collaborate in requirement analysis, story refinement, and solution design activities.
• Estimate and deliver assigned work within Agile development cycles.
• Build agentic applications, AI assistants, workflow automation capabilities, and event‑driven services using Kafka, containers, and MCP architectures.
• Deliver secure, scalable, observable, and resilient software solutions aligned with enterprise standards.
• Troubleshoot, optimize, and maintain platform services to ensure operational excellence.

• Bachelor’s computer science, Engineering, Data Science, or job related field required.
• 6+ years of software engineering experience with strong expertise in Python‑based application development.
• Experience developing AI/ML, Data Science, Data Engineering, or analytics applications in enterprise environments.
• Strong understanding of modern Generative AI and Data Science platform architectures, including…