Software Engineer III (ai/ml)

Bank of America Bank of America · Banking · Plano, TX

Software Engineer III (AI/ML) at Bank of America, working on the Erica, Chat, and Voice Technology team. The role involves designing, developing, and supporting scalable software solutions and AI-powered applications, including Generative AI and RAG. Requires strong software engineering fundamentals and experience with modern AI/ML technologies.

What you'd actually do

  1. Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
  2. Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
  3. Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
  4. Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
  5. Performs spike/proof of concept as necessary to mitigate risk or implement new ideas

Skills

Required

  • 3+ years of software development experience using Java, Python, or related technologies.
  • Strong object-oriented programming and software design skills.
  • Experience building enterprise applications and RESTful web services.
  • Knowledge of AI/ML concepts and experience developing AI-enabled applications.
  • Familiarity with Large Language Models (LLMs), Generative AI, and modern AI frameworks.
  • Experience implementing Retrieval Augmented Generation (RAG) solutions and retrieval techniques.
  • Experience working with source control tools such as Git.
  • Strong analytical and problem-solving skills.
  • Good verbal and written communication skills.
  • Experience working in Agile development environments.

Nice to have

  • Experience with Elasticsearch, OpenSearch, SOLR, or similar search platforms.
  • Experience with AI/ML frameworks and model integration.
  • Experience with vector databases, embeddings, and semantic search.
  • Experience with Kubernetes, Docker, and containerized deployments.
  • Experience with cloud platforms such as Azure or AWS.
  • Experience with Cassandra, Redis, or other distributed data technologies.
  • Understanding of MLOps, model deployment, monitoring, and observability concepts.
  • Experience with chatbot, conversational AI, or virtual assistant platforms.
  • Experience with prompt engineering and model evaluation techniques.
  • Experience with GPU-based AI workloads and inference platforms.

What the JD emphasized

  • compliance requirements
  • AI/ML concepts
  • Large Language Models (LLMs), Generative AI
  • Retrieval Augmented Generation (RAG) solutions
  • Retrieval Augmented Generation (RAG) solutions and retrieval techniques

Other signals

  • Develop and integrate AI/ML-powered capabilities into enterprise applications.
  • Support implementation of Generative AI and Retrieval Augmented Generation (RAG) solutions.
  • Familiarity with Large Language Models (LLMs), Generative AI, and modern AI frameworks.
  • Experience implementing Retrieval Augmented Generation (RAG) solutions and retrieval techniques.