Software Engineer III (AI/ML)

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.

LOB Position Summary This position is part of Bank of America's Erica, Chat, and Voice Technology organization. The team builds next-generation AI, Search, and Conversational platforms that power virtual financial assistant and search capabilities across multiple channels. Candidate will design, develop, test, and support scalable software solutions and AI-powered applications.

The role requires strong software engineering fundamentals, experience working with modern AI/ML technologies, and the ability to collaborate effectively within an Agile delivery team.

- 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) - Implement high-quality code following enterprise standards, architecture patterns, and engineering best practices. - Participate in solution design discussions and contribute to technical implementation decisions. - Develop and integrate AI/ML-powered capabilities into enterprise applications. - Support implementation of Generative AI and Retrieval Augmented Generation (RAG) solutions. - Develop and maintain RESTful APIs, microservices, and backend services. - Perform code reviews and contribute to continuous improvement of engineering practices. - Troubleshoot, debug, and resolve application and production issues. - Ensure solutions meet security, performance, scalability, and reliability requirements. - Collaborate with product owners, architects, and engineering teams to deliver business requirements. - Support deployment, monitoring, and optimization of applications across enterprise environments. - Participate in Agile ceremonies including sprint planning, estimation, and retrospectives.

- 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.

- 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.