Treasury AI & ML Engineering Leader

Treasury AI & ML Engineering Leader

Full-Time 81000 - 99000 Β£ / year (est.) No working from home possible
eFinancialCareers

At a Glance

  • Tasks: Lead the adoption of AI and ML in Treasury, driving innovation and real-time data solutions.
  • Company: Join a forward-thinking financial institution focused on technology and transformation.
  • Benefits: Competitive salary, professional development, and opportunities for mentorship.
  • Other info: Collaborative environment with a focus on continuous learning and knowledge sharing.
  • Why this job: Shape the future of banking with cutting-edge AI technologies and impactful leadership.
  • Qualifications: Experience in AI/ML, strong leadership skills, and a passion for innovation.

The predicted salary is between 81000 - 99000 Β£ per year.

e Financial Careers is seeking a Treasury AI Engineering Lead to drive adoption and scaling of Generative AI and ML within Treasury, transforming it into a real-time, data-driven partner.

You will guide architectural decisions, mentor engineers, and ensure high-quality, tested solutions across platforms.

The role emphasizes leadership in both banking and technology, with stakeholder management and ongoing learning, fostering innovation and knowledge sharing across teams and external communities.

#J-18808-Ljbffr

Treasury AI & ML Engineering Leader employer: eFinancialCareers

Quilter plc is an exceptional employer, offering a dynamic work environment in Southampton where innovation and collaboration thrive. With a strong commitment to employee growth, comprehensive benefits including a generous holiday allowance and a non-contributory pension scheme, Quilter fosters a culture of inclusivity and continuous improvement, empowering employees to make meaningful contributions to the financial futures of their clients and communities.

eFinancialCareers

Contact Details:

eFinancialCareers Recruitment Team

We think you need these skills to ace Treasury AI & ML Engineering Leader

Generative AI
Machine Learning (ML)
Architectural Decision-Making
Mentoring
Quality Assurance
Stakeholder Management
Leadership