AI Engineer - Data Scientist I

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

The Data and AI team within Global Payment Solutions (GPS) at Bank of America is looking for an AI Engineer who is a self-starter, thrives on solving ambiguous problems, and can translate advances in artificial intelligence into scalable, production-ready products. 

Who we are:

The GPS Data and AI team drives and powers innovation within the one of the largest payment businesses in the world. We are a team of data scientists and engineers building end-to-end AI and data solutions that operate at scale. We welcome challenging and ambiguous problems because that is where innovation begins. Many of our projects start with "think tank" sessions alongside business teams, where we identify high-impact opportunities and translate them into tangible AI-powered solutions and products. 

Our work spans Generative AI, information retrieval, intelligent agents, machine learning, natural language processing, optimization, and predictive modeling, with a strong focus on turning emerging AI capabilities into solutions that create measurable business value. 

Representative Projects:

• Develop advanced statistical methods to determine the optimal interest-rate or product pricing strategies for clients
• Build a Generative AI-powered search platform that enables sales and product teams to access high quality answers to product, servicing, and client related questions
• Develop AI models that shift foreign currency conversion “up the payment stream,” reducing reliability on beneficiary banks
• Apply advanced NLP techniques to generate near real-time insights into what clients are reaching out to servicing teams about, helping servicing teams anticipate client needs and improve service quality

Your role:

As an AI Engineer on the GPS Data and AI team, you will help design and build the next generation of AI-powered products used across the business. This role sits at the intersection of AI research, software engineering, and product development. You will take emerging techniques in Generative AI and machine learning and translate them into robust systems capable of operating in a complex enterprise environment. You will work across the AI application stack, from experimentation and prototyping through evaluation, optimization, deployment, and production monitoring. You will design intelligent applications using LLMs, RAG, information retrieval, and machine learning, while developing the infrastructure and software needed to make those systems reliable and scalable. 

Skills and Qualifications:

Required: 

• Minimum Bachelor’s degree in a quantitative or technical field such as computer science, math, statistics, physics, or a related discipline 
• Minimum 2 years of experience developing production-quality software, machine learning systems, or AI-powered applications using Python and/or C++
• Strong foundation in probability, statistics, and applied machine learning (NLP, time-series analysis, GenAI)
• Strong understanding of software engineering fundamental, including modular system design, APIs, testing, version control, and maintainable production code 
• Ability to communicate complex technical concepts clearly and concisely to both technical and non-technical stakeholders

Nice to have:

• Graduate degree in computer science, engineering, mathematics, statistics, physics, or another quantitative field.
• Hands-on experience building RAG systems, AI agents, LLM applications, or multimodal AI systems.
• Exposure to reinforcement learning, recommendation systems, optimization, or time-series modeling.
• Energized by the pace and ambiguity of a dynamic environment and comfortable rapidly learning unfamiliar technical areas.

Responsibilities:

• Frame abstract business problems using advanced data science and machine learning algorithms 
• Own AI systems end-to-end, from initial research and prototyping through architecture, implementation, evaluation, deployment, and ongoing improvement.
• Experiment with new models, retrieval strategies, prompting techniques, agent architectures, and emerging AI technologies to determine their applicability to real-world business problems.
• Develop rigorous evaluation frameworks to measure AI system quality and identify opportunities for improvement.
• Partner with product, engineering, and business stakeholders to translate ambiguous business challenges into well-defined AI solutions.
• Shape cross-team collaboration to advance the firm's data science and AI capabilities

Skills:

• Adaptability
• Attention to Detail
• Business Analytics
• Technical Documentation
• Written Communications
• Agile Practices
• Application Development
• Collaboration
• Data Visualization
• DevOps Practices
• Artificial Intelligence/Machine Learning
• Networking
• Policies, Procedures, and Guidelines Management
• Presentation Skills
• Risk Management

Shift:

1st shift (United States of America)

Hours Per Week: 

40