Senior Vice President, AI / Machine Learning Data Engineer

We’re seeking a future team member for the role of SVP, AI / Machine Learning Data Engineer to join our AI Hub team. This role is located in New York City, NY or Lake Mary, FL.

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 a strong opportunity for a hands-on technical lead who can apply deep AI and software engineering expertise to deliver practical solutions, guide technical direction, and help scale high-value capabilities in an enterprise environment.

In this role, you’ll make an impact in the following ways:

• Lead research initiatives hands-on, provide direction on AI solutions, technical expertise, and craft strategic approaches for Machine Learning and Artificial Intelligence products.
• Bring deep knowledge of Applied AI, LLMs, fine tuning and approaches to creating fit-for-purpose models and agents.
• Conduct technical research studies to provide additional facts needed to make informed strategic decisions.
• Establish strong relationships with internal teams to gain an understanding of their strategies, objectives, and tactics to develop a comprehensive success measurement plan.
• Bring expertise in leveraging AI to create effective software lifecycles and empower builders, designers and developers.
• Contributing to the achievement of Application Development objectives. Mentors and develops a successful team of machine learning engineers.

To be successful in this role, we’re seeking the following:

• Bachelor’s degree in computer science engineering or a related discipline, or equivalent work experience required.
• 9-11 years of experience in software development required; experience in the securities or financial services industry is a plus.
• Advanced experience (preferably 9+ years) in applied AI/ML, modelling and software engineering.
• Ability to operate as a group technical lead, collaborating with, mentoring and guiding the direction of engineers or researchers.
• Strong understanding of enterprise software practices and how to create sustainable architectures.
• Ability to communicate technical ideas and express complex concepts to different types of audiences.