VP, AI & ML Data Engineering

Archer; Manchester; On-site; GBP 120,000 - 180,000; Full time

Job summary

BNY is seeking a Vice President, AI / Machine Learning Data Engineer to join its Finance Engineering team in Manchester. This role focuses on designing and building AI-driven solutions for enterprise data problems across the full lifecycle from problem framing to deployment.

The ideal candidate will have strong analytical and ML knowledge, be able to design scalable AI systems, and translate complex business problems into algorithmic solutions while collaborating with cross-functional teams in a

Qualifications

• Degree in Computer Science, Mathematics, AI, Data Science, or related quantitative field.
• Experience in software development with AI-based frameworks.
• Strong analytical and algorithmic problem-solving skills.

Responsibilities

• Design and develop AI-powered solutions for complex enterprise data problems.
• Translate ambiguous business problems into structured AI/ML approaches and algorithms.
• Build scalable architectures for AI solutions, including model pipelines, data processing, and decision systems.
• Collaborate with platform, data, and product teams to integrate AI capabilities into enterprise systems.
• Evaluate and experiment with emerging AI methodologies and frameworks to improve solution effectiveness.
• Document solution design, assumptions, and algorithms for enterprise adoption.

Skills

AI/ML concepts

Algorithmic thinking

System design

Data processing

Communication

Education

Bachelor's degree in CS/Math/AI/Data Science

Job description

BNY is seeking a Vice President, AI / Machine Learning Data Engineer to join its Finance Engineering team in Manchester. This role focuses on designing and building AI-driven solutions for enterprise data problems across the full lifecycle from problem framing to deployment.

The ideal candidate will have strong analytical and ML knowledge, be able to design scalable AI systems, and translate complex business problems into algorithmic solutions while collaborating with cross-functional teams in a