Director, AI / Machine Learning Data Engineer

BNY Mellon•New York, NY

1d•Onsite

About The Position

We’re seeking a future team member for the role of Director, AI / Machine Learning Engineer to join our AI Hub team. This role is located in New York, NY. This role is located in our AI Hub and is focused on building AI-powered tools and platforms that improve the way engineers design, build, test, and operate software. This is an opportunity for a highly technical individual contributor to apply deep expertise in AI/ML and software engineering to build practical, scalable solutions that improve developer productivity, accelerate software delivery, and drive measurable impact across the enterprise. The ideal candidate combines hands-on engineering excellence with strong technical judgment, a passion for innovation, and the ability to translate emerging AI capabilities into production-ready solutions. In this role, you’ll make an impact in the following ways: Design, develop, and deliver enterprise-scale AI/ML solutions, intelligent applications, backend services, and data products that address complex business challenges and create measurable value. Contribute to the architecture, design, and implementation of machine learning, generative AI, data science, and software engineering solutions, ensuring scalability, performance, reliability, and maintainability. Drive the development of production-grade AI/ML and software solutions across the full lifecycle, including solution design, coding, testing, deployment, monitoring, and continuous optimization. Develop high-quality, secure, and efficient code while applying engineering best practices, conducting code reviews, and proactively managing technical debt. Design, build, and maintain enterprise data pipelines and integrations, ensuring the quality, availability, and effective use of strategic data assets. Partner with business stakeholders, product teams, and engineering organizations to translate business requirements into scalable technical solutions and resolve complex technical challenges. Apply security, privacy, governance, and responsible AI principles throughout the development lifecycle to deliver trusted and compliant solutions. Leverage deep expertise in AI/ML, data engineering, cloud technologies, and distributed systems to influence technical direction and drive engineering excellence. Evaluate and adopt emerging technologies, tools, and methodologies to advance the organization's AI capabilities and accelerate innovation. Communicate technical strategies and solution recommendations to business and technology leaders while fostering technical excellence through knowledge sharing and mentorship.

Requirements

Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required; advanced degree is beneficial.
12+ years of experience in software development required; experience in the securities or financial services industry is a plus.
Advanced experience, preferably 10+ years, in applied AI/ML, model development, and software engineering, including experience deploying solutions into production environments.
Strong understanding of enterprise software practices, MLOps / LLMOps, evaluation frameworks, and how to create secure, scalable, and sustainable AI architectures.
Ability to communicate technical ideas clearly and influence a range of audiences, including engineers, product partners, and senior business stakeholders.

Nice To Haves

Advanced degree is beneficial.
Experience in the securities or financial services industry is a plus.

Responsibilities

Design, develop, and deliver enterprise-scale AI/ML solutions, intelligent applications, backend services, and data products that address complex business challenges and create measurable value.
Contribute to the architecture, design, and implementation of machine learning, generative AI, data science, and software engineering solutions, ensuring scalability, performance, reliability, and maintainability.
Drive the development of production-grade AI/ML and software solutions across the full lifecycle, including solution design, coding, testing, deployment, monitoring, and continuous optimization.
Develop high-quality, secure, and efficient code while applying engineering best practices, conducting code reviews, and proactively managing technical debt.
Design, build, and maintain enterprise data pipelines and integrations, ensuring the quality, availability, and effective use of strategic data assets.
Partner with business stakeholders, product teams, and engineering organizations to translate business requirements into scalable technical solutions and resolve complex technical challenges.
Apply security, privacy, governance, and responsible AI principles throughout the development lifecycle to deliver trusted and compliant solutions.
Leverage deep expertise in AI/ML, data engineering, cloud technologies, and distributed systems to influence technical direction and drive engineering excellence.
Evaluate and adopt emerging technologies, tools, and methodologies to advance the organization's AI capabilities and accelerate innovation.
Communicate technical strategies and solution recommendations to business and technology leaders while fostering technical excellence through knowledge sharing and mentorship.