VP, AI/ML Data Engineer — Enterprise AI Architect

BNY; Manchester; On-site; GBP 120,000 - 170,000; Full time

Job summary

BNY in Manchester is seeking a Vice President, AI / Machine Learning Data Engineer to lead the design and delivery of AI-driven data solutions across complex enterprise platforms. You’ll bridge business problems and scalable AI architectures, guiding model pipelines, data processing, and orchestration with cross-functional teams.

Ideal candidates hold a quantitative degree, strong software development experience, and deep knowledge of ML concepts, algorithms, and evaluation frameworks.

Qualifications

• Degree in Computer Science, Mathematics, AI, Data Science, or related quantitative field.
• Strong software development experience with AI frameworks.
• Solid understanding of ML concepts, statistics, and AI techniques.

Responsibilities

• Design and develop AI-powered solutions to solve complex enterprise data and analytics 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

Analytical skills

System design

Model pipelines

Data processing

Algorithmic thinking

Problem translation

Large datasets

Communication skills

Software development

Education

Degree in Computer Science/Mathematics/AI/Data Science

Tools

Python

Job description

BNY in Manchester is seeking a Vice President, AI / Machine Learning Data Engineer to lead the design and delivery of AI-driven data solutions across complex enterprise platforms. You’ll bridge business problems and scalable AI architectures, guiding model pipelines, data processing, and orchestration with cross-functional teams.

Ideal candidates hold a quantitative degree, strong software development experience, and deep knowledge of ML concepts, algorithms, and evaluation frameworks.