Software Engineer I A - GBS IND

Bank of America is seeking a Software Engineer (AI Agent & Data/ML) to design, develop, and operate AI agents, large-scale data pipelines, and machine learning solutions to support enterprise automation and analytics initiatives. This role requires strong engineering skills, expertise in LLM and agentic architecture, and the ability to deploy AI systems securely and reliably within a regulated environment.

• 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)

• 3+ years of experience in Data Engineering, ML Engineering, AI Engineering, or Software Engineering
• Strong proficiency in Python, SQL, and one additional programming language (Scala/Java/Go)
• Hands-on experience designing AI agents, tool chains, and agent frameworks (LangChain, Semantic Kernel, LlamaIndex, AutoGen, etc.)
• Strong understanding of LLM integration, function-calling patterns, prompt engineering, and agent orchestration
• Experience deploying ML models using MLflow, Azure ML, SageMaker, Kubeflow, or similar
• Proficiency in TensorFlow, PyTorch, Scikit-Learn, or equivalent ML frameworks
• Experience building scalable data pipelines using Spark, Databricks, or similar technologies
• Strong knowledge of RAG patterns, vector databases (FAISS, Pinecone, Chroma, Milvus, Redis), and embedding optimization
• Experience with CI/CD pipelines, automated testing, code reviews, and deployment automation
• Familiarity with containerization (Docker) and orchestration (Kubernetes)