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Senior Python Developer - Quant Models AI Automation, Vice President

Citi -
London

Apply Now

Job details

Full-time
1 day ago

Qualifications

Law
Computer Science
Stakeholder collaboration
Mentoring junior staff
Engineering
NumPy
Kubernetes orchestration
Test automation
Mathematics
Software development operations experience
Master's degree
Application development
Pandas
Docker
CI/CD pipelines
Machine learning
Mentoring
Physics
Multidisciplinary collaboration
AI

Full job description

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

We are seeking a senior Python Developer within Risk Technology to join a multi-year strategic initiative: the design and delivery of AI-enabled automation across the end-to-end quantitative model lifecycle, covering all market risk and credit risk models.

This is a hands-on engineering role at the core of the program. You will design and build the tooling and services that power AI-assisted model documentation, automated model testing and validation workflows, large-scale risk data analysis, and model lifecycle management. You will work closely with quantitative analysts, model validators, data engineers, and the program leadership to translate workflow automation requirements into robust, production-grade solutions.

Key Responsibilities

Engineering & Delivery

Design, develop, and maintain Python-based services, pipelines, and tools supporting automation of the quantitative model lifecycle across market risk and credit risk model families.
Build and operate automated testing and validation frameworks for quantitative models, including test orchestration, result capture, benchmarking, and reporting.
Develop data analysis and reconciliation tooling over large-scale risk datasets, ensuring data quality, lineage, and traceability across risk platforms.

AI Enablement

Implement AI/ML components within the model workflow, including LLM-based automation for model documentation generation and updating, intelligent data quality checks, and workflow assistance.
Integrate AI tooling into a controlled, auditable, production-grade environment, with appropriate testing, monitoring, and governance controls.

Collaboration & Standards

Work within a cross-functional agile team alongside quants, validators, data engineers, and program management.
Promote engineering best practices: code quality, testing, CI/CD, documentation, and secure, scalable design.

Required Qualifications

STEM degree (Computer Science, Engineering, Mathematics, Statistics, Physics, or related); Master's degree preferred.
Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools).
Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services experience strongly preferred.
Solid AI/ML knowledge, including practical experience with machine learning libraries and/or LLM-based application development (e.g., API integration, prompt engineering, RAG-style document workflows).
Strong experience with test automation, CI/CD, and modern software engineering practices (Git, code review, containerization).
Experience working with large datasets, data quality/linearity checks, and SQL; familiarity with enterprise data platforms.
Ability to work effectively in a cross-functional, global team and communicate technical concepts to non-technical stakeholders.

Preferred Qualifications

Exposure to quantitative risk models (market risk and/or credit risk) and the model lifecycle: development, validation, documentation, and ongoing monitoring.
Familiarity with the model risk regulatory landscape and governance expectations in banking.
Experience with workflow orchestration platforms, cloud environments (AWS/Google Cloud), and container orchestration (Docker/Kubernetes).
Background in quantitative finance, statistics, or data science; an advanced quantitative degree is a plus.
Experience mentoring engineers and leading small technical workstreams.

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

Apply Now

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