BNY is looking to leverage cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. The AI Engineer will support Mainframe modernization initiatives by applying automation and analytics and embedding automation and AI-assisted capabilities within modernized platforms.
Requirements
- Strong proficiency in Python and Java programming
- Experience with DevOps tools and practices (e.g., CI/CD pipelines, containerization, automation frameworks)
- Strong data handling and analysis skills using pandas and numpy
- Solid familiarity with machine learning and deep learning principles
- Experience with ML frameworks such as scikit-learn, TensorFlow, and PyTorch
- Exposure to Generative AI tools (OpenAI API, LangChain, prompt engineering)
- Comfort with rapid prototyping and iterative development
Responsibilities
- Develop, prototype, and deploy scalable software solutions using Java and Python.
- Support Mainframe modernization initiatives by applying automation and analytics.
- Implement and maintain CI/CD pipelines and DevOps practices to ensure smooth deployment and operation of applications.
- Collaborate with data science, infrastructure and engineering teams to embed automation and AI-assisted capabilities within modernized platforms.
- Apply familiarity with AI/ML tools and concepts to support solution development.
- Stay current with emerging Java technologies, Python scripting, DevOps tools, and AI/ML trends to continuously improve solutions and support modernization goals
Other
- 7-9 years of experience in software development required; experience in the securities or financial services industry is a plus.
- Industry experience (3 – 4 yrs) strongly preferred
- Communicate technical concepts clearly and effectively to diverse audiences.
- Work independently and as part of a team to iterate rapidly on prototypes and solutions.
- Clear and effective verbal communication
- Ability to work independently and collaboratively in a team environment
