Bulge Bracket Investment Banks

Posted 10 days ago

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**Applied AI ML Lead Engineer, VP - Asset and Wealth Management** Leverage approved AI-assisted tools to drive quality, accelerate delivery, and enhance operational resilience. Lead the adoption of secure coding, automated testing, and AI-driven workflows. Define and establish validation standards for AI-assisted work. Collaborate with senior engineers and stakeholders to plan and execute enterprise-wide AI strategies. Requires extensive experience in AI-assisted software development, AWS, software design, CI/CD pipelines, and Python. Familiarity with prompt engineering, RAG-based architecture, and Terraform is a plus.

Compensation: Not specified
City: London
Country: United Kingdom

Full Job Description

Location: LONDON, United Kingdom

We have an opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful ownership and growth here.

As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will be a core technical contributor on an agile team, delivering critical technology solutions across multiple technical areas. You will help advance engineering outcomes by enabling responsible, compliant, and effective use of approved AI-assisted development practices.

Job Responsibilities

Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes

Establish validation standards for AI-assisted work, including secure coding, peer review, and automated testing

Promote reuse of effective patterns across the team to improve consistency and reliability

Apply software development lifecycle tools, including approved AI-assisted development and automation capabilities, to increase the value realized from automation

Required Qualifications, Capabilities, and Skills

Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting

Ability to set team expectations for validating AI outputs for correctness, performance, and security

Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations

Experience coaching engineers on safe, compliant adoption of AI-assisted practices within delivery workflows

Knowledge of the financial services industry and its technology systems

Proficiency in Python or an equivalent programming language

Experience working in AWS or an equivalent cloud environment, with understanding of Terraform, EKS, and ECS

Strong knowledge of system and application design

Familiarity with CI/CD pipelines and software development lifecycles

Experience with prompt engineering and retrieval-augmented generation (RAG) based architecture

Ability to communicate with clarity and credibility across senior engineers, stakeholders, and product partners

Preferred Qualifications, Capabilities, and Skills

Experience building agentic tools and AI agents that support engineering workflows in production environments

Experience with Airflow

Lead approved AI-assisted engineering practices to improve quality, delivery speed, and operational resilience.

Full Job Description

Location: LONDON, United Kingdom

Job Responsibilities

Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes

Establish validation standards for AI-assisted work, including secure coding, peer review, and automated testing

Promote reuse of effective patterns across the team to improve consistency and reliability

Apply software development lifecycle tools, including approved AI-assisted development and automation capabilities, to increase the value realized from automation

Required Qualifications, Capabilities, and Skills

Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting

Ability to set team expectations for validating AI outputs for correctness, performance, and security

Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations

Experience coaching engineers on safe, compliant adoption of AI-assisted practices within delivery workflows

Knowledge of the financial services industry and its technology systems

Proficiency in Python or an equivalent programming language

Experience working in AWS or an equivalent cloud environment, with understanding of Terraform, EKS, and ECS

Strong knowledge of system and application design

Familiarity with CI/CD pipelines and software development lifecycles

Experience with prompt engineering and retrieval-augmented generation (RAG) based architecture

Ability to communicate with clarity and credibility across senior engineers, stakeholders, and product partners

Preferred Qualifications, Capabilities, and Skills

Experience building agentic tools and AI agents that support engineering workflows in production environments

Experience with Airflow

Lead approved AI-assisted engineering practices to improve quality, delivery speed, and operational resilience.

Applied AI ML Lead Engineer, VP - Asset and Wealth Management

Full Job Description

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