Software Engineer II (AI/ML)

Bank of America•Plano, TX

2d•Onsite

About The Position

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, coding solutions, unit testing, and ensuring the solution can be integrated successfully into the overall application/system with clear, robust, and well-tested interfaces. Job expectations include an awareness of development and testing practices in the industry. This position is part of Bank of America's Erica, Chat, and Voice Technology organization, the team behind one of the bank's most strategic and visible AI-powered platforms. Erica serves millions of clients across digital channels and is at the forefront of transforming how customers interact with Bank of America through conversational AI, intelligent search, personalized insights, and virtual assistance. As part of the Erica engineering team, you will help build the next generation of AI-driven experiences, leveraging cutting-edge technologies including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent search, agent-based architectures, and enterprise-scale AI platforms. This role provides a unique opportunity to work on high-impact initiatives that directly influence client engagement, digital adoption, and the future of AI-powered banking. You will collaborate with experienced engineers, architects, data scientists, and product leaders to develop scalable, secure, and resilient solutions that operate at enterprise scale. The work spans AI platform engineering, conversational experiences, intelligent orchestration, search technologies, and modern cloud-native software development. This is an excellent opportunity for engineers who are passionate about innovation, interested in solving complex technical challenges, and excited to contribute to one of the financial industry's leading AI and digital transformation programs. The candidate will design, develop, test, and support scalable software platforms and AI-powered applications that enable the future of conversational banking and personalized client experiences. The role combines strong software engineering fundamentals with modern AI application development, offering hands-on experience building enterprise solutions powered by Generative AI, LLMs, intelligent search, and machine learning technologies. Engineers in this role will contribute to critical initiatives that help shape the evolution of Erica and Bank of America's next-generation digital experiences. The successful candidate will: Work on one of the banking industry's most recognized AI-powered virtual assistants. Help shape the future of AI and digital experiences for millions of Bank of America clients. Contribute to strategic initiatives involving Generative AI, LLMs, RAG, intelligent search, and conversational platforms. Partner with industry-leading engineers, architects, data scientists, and AI specialists. Gain exposure to modern software engineering practices, cloud-native architectures, and enterprise-scale AI systems. Tackle challenging technical problems with direct business impact and executive visibility.

Requirements

1+ 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 Haves

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.

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)
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.