Treasury AI Engineering Lead

NatWest Group

Greater London

On-site

GBP 100,000 - 150,000

Full time

14 days+
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Job summary

NatWest Group is seeking a Treasury AI Engineering Lead to drive the adoption and scaling of Generative AI and ML within Treasury, transforming it into a data-driven business partner. You will design software and tools aligned with strategy, and ensure quality through automated testing.

You will lead a team of engineers, research emerging technologies, and share insights with the innovation community to maintain cutting-edge capabilities across the function.

Qualifications

  • Proven experience in AI or ML engineering, MLOps, or cloud-based analytics, ideally within financial services.
  • Excellent communication and stakeholder management skills, with the ability to bridge technical and business domains.
  • A collaborative, adaptable approach and commitment to continuous learning and improvement.
  • A deep understanding of a wide range of programming languages and technical domains.
  • Experience of architecture design principles across bank-wide production.

Responsibilities

  • Design AI and ML solutions for Treasury use cases, such as liquidity forecasting, capital optimisation, and risk management.
  • Overseeing the migration to secure, scalable cloud-based environments, enabling experimentation and prototyping.
  • Championing robust data strategy and governance, ensuring quality, accessibility, and security.
  • Fostering an agile, innovative culture and mentoring Treasury colleagues in AI engineering and responsible AI practices.

Skills

AI/ML engineering
MLOps
Cloud analytics
Leadership
Stakeholder management
Communication

Job description

Join us as an Treasury AI Engineering Lead

  • In this key role, you’ll lead the adoption and scaling of Generative AI and advanced machine learning (ML) within Treasury to transform our function into a predictive, real-time, and data-driven business partner

  • You’ll add real value by building and sharing your technical expertise, staying updated on innovations, and promoting knowledge across the team and the wider technical community

  • You’ll be playing a significant part in designing software and tools that align with the strategic vision and project objectives, ensuring they meet all the requirements through thorough research

  • We’ll look to you to deliver the highest quality solutions using automated unit, system, and integration testing

What you'll do

As a Treasury AI Engineering Lead, you’ll be overseeing our strategic vision by researching and implementing emerging technologies, assessing opportunities and risks, and leading a team of engineers to address key priorities. You’ll also be keeping the innovation team and the wider technical audience informed by sharing your insights into the latest industry trends.

In addition, you’ll be:

  • Designing and delivering AI and ML solutions for Treasury use cases, such as liquidity forecasting, capital optimisation, and risk management

  • Overseeing the migration to secure, scalable cloud-based environments, enabling experimentation and prototyping

  • Championing robust data strategy and governance, ensuring quality, accessibility, and security

  • Fostering an agile, innovative culture and mentoring Treasury colleagues in AI engineering and responsible AI practices

The skills you'll need

We’re looking for someone with leadership experience in both banking and technology sectors, along with a deep awareness of the latest technology industry developments. Working closely with executives and stakeholders, we’ll look to you to have exceptional stakeholder management skills and the ability to influence and align diverse interests towards a shared goal.

To succeed in this role, you’ll also need excel as an innovation professional across the global innovation ecosystem.

In addition, you must have:

  • Proven experience in AI or ML engineering, MLOps, or cloud-based analytics, ideally within financial services

  • Excellent communication and stakeholder management skills, with the ability to bridge technical and business domains

  • A collaborative, adaptable approach and commitment to continuous learning and improvement

  • A deep understanding of a wide range of programming languages and technical domains

  • Experience of architecture design principles across bank-wide production

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