Bank of America currently has 20 active AI-related job listings. The majority of these roles, 70%, are focused on agents, with post-training and data roles each comprising 10%. Engineering is the dominant function, with 18 listings. Recent hiring trends show a significant increase, with 14 new AI roles posted in the last 30 days, representing a 180% increase from the prior 30-day period.
Currently tracking 15 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $105k–$246k (avg $192k).
Bank of America currently has 23 active AI-related roles in our index. The most common open titles are: Artificial Intelligence Senior Security Engineer, Corporate Security Professional - Corporate Security Technology Innovation Manager, Data Scientist I, Data Scientist II, Director; Senior Architect. Most positions are in Engineering and Research.
Bank of America's active AI hiring is concentrated in: agents (57%), data (17%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Bank of America is hiring AI talent in: United States (22 roles).
Job postings at Bank of America most frequently mention: System Design, AI Safety, Statistics, Large Language Models (LLMs), Generative AI.
In the past 30 days, Bank of America has posted 17 new AI-related roles. That is a +89% change versus the prior 30 days (9 → 17).
| Title | Stage | AI score |
|---|---|---|
| Vice President; Quantitative Finance Analyst Develops and maintains statistical and machine learning models for financial crime and money laundering detection, involving data mining, feature engineering, and ensuring regulatory compliance. Supports cross-functional teams in building analytical solutions and drives innovation by evaluating new AI/ML techniques. | Post-train | 7 |
| : Vice President; Sr Quantitative Fin Analyst This role involves conducting quantitative analytics and complex modeling projects, with a focus on validating financial crime detection models using machine learning and deep learning techniques. The position requires experience in independent model validation, regulatory compliance, and providing governance oversight for financial crime detection models. | Post-train |
| 7 |
| VP, Quant Analyst - Central Modelling Solutions Team VP-level Quant Analyst role focused on developing and implementing quantitative models, including machine learning models, for XVA trading desks across various asset classes. Requires strong programming skills in Python and C++, and expertise in financial modeling, option pricing, stochastic calculus, and statistics. The role involves front-office pricing, automated hedging, and optimization, with implementation in Python and C++. | Post-trainServe | 7 |