Applied AI ML Lead- Agentic AI & Python

Overview

In this role you will drive end-to-end IPB AI/ML use cases from problem framing to production deployment, delivering measurable advisor and client impact. You will lead the engineering build of agentic AI and LLM-powered products for IPB clients worldwide, while setting high engineering quality standards. You will establish Responsible AI controls and governance-aligned practices to ensure safe, scalable solutions. You will partner with senior stakeholders across IPB, influence funded workstreams, and contribute to GenAI education within the team. This is a chance to shape AI at scale in a global private banking context, balancing innovation with risk management.

Responsibilities

• Own end-to-end delivery of priority IPB AI/ML use cases from framing to deployed production services with measurable impact
• Lead engineering build of agentic AI and LLM-powered products for IPB advisors and clients globally
• Set engineering quality through code reviews, technical design, and pairing with peers and junior engineers
• Establish Responsible AI controls in production (guardrails, evaluation frameworks, observability, model risk controls)
• Act as primary technical partner to IPB business stakeholders and shape AI/ML opportunities into funded workstreams
• Represent AIML in firm-wide AI/ML governance and ensure regulatory and data-privacy considerations are reflected in design
• Contribute to GenAI education programme via training content and mentoring
• Champion diversity, opportunity, inclusion, and respect

Key requirements

• Formal training or certification in software engineering concepts and expert applied experience
• Advanced proficiency in Python and modern software engineering practices
• Fluent with AI coding tools (Claude Code, GitHub Copilot)
• Hands-on experience building, evaluating, and deploying ML models into production
• Practical experience with Large Language Models (prompt engineering, RAG, fine-tuning, agentic frameworks)
• Experience delivering system design, application development, testing, and operational stability for ML or data-intensive systems
• Strong communication skills for senior stakeholders and translating technical concepts
• Experience applying new methods to solve complex technology problems across multiple disciplines
• MSc in Computer Science, Data Science, Engineering, or related quantitative field

• strong communication
• stakeholder collaboration
• mentoring and coaching
• Python
• CI/CD
• containerization

Full job description from WhatJobs. Apply for this role →