Lead Applied AI Engineer - Banking Technology, Senior Vice President

Citi · citibenefits.com

London United Kingdom Full-time today
Workplace
On-site
Location
London United Kingdom
Who can apply
Based in the United Kingdom: you usually need the right to work there

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About the role

Role Overview

We are seeking an AI‑first Lead AI Engineer to define, architect, and deliver enterprise‑scale AI solutions for Investment, Corporate, and Commercial Banking.

This role combines deep hands‑on technical leadership with architectural ownership, driving the adoption of LLMs, agentic workflows, and generative AI platforms to improve efficiency, automation, simplification, and risk reduction. The Lead AI Engineer will shape both technical delivery and AI-first engineering culture, partnering closely with multiple technology and business teams.

Key Responsibilities

* End‑to‑End AI Leadership: Lead the design, hands‑on implementation, and deployment of scalable agentic AI and generative AI solutions for high‑impact business use cases. * Agentic Architecture: Architect advanced agent‑based systems (perception, reasoning, planning, execution), integrating multiple LLM providers (OpenAI, Anthropic, Google). * Full‑Stack AI Engineering: Build and deliver production‑grade, full‑stack AI applications using modern ML/LLM platforms and AI coding tools (e.g., Devin, GitHub Copilot). * Rapid Value Delivery: Champion MVP‑driven delivery, rapid iteration, hypothesis testing, and experimentation (A/B testing) to achieve fast time‑to‑value. * Evaluation & Optimization: Define rigorous evaluation frameworks and metrics for AI and agent performance, ensuring continuous optimization and alignment with business goals. * Technology Foresight: Proactively evaluate and integrate emerging AI technologies, particularly in agent‑based and autonomous AI systems, while acting as a thought leader and coach. * Technical Leadership & Mentorship: Provide front‑line technical leadership, guide architectural decisions, and mentor engineers across AI, data, and application teams to build an AI‑first engineering culture. * Strategic Domain Alignment: Ensure all AI solutions are grounded in deep banking domain understanding and clearly articulate business and risk impact beyond pure technical implementation.

Qualifications

- Programming: Expert‑level proficiency in Python and/or Java (Spring Boot); solid experience with JavaScript/TypeScript (Angular, Node.js).

- AI/ML Expertise:

* Deep knowledge of AI fundamentals (knowledge representation, automated planning, decision‑making under uncertainty, multi‑agent systems). * Extensive hands‑on experience with LLM platforms (OpenAI, Anthropic, Google), RAG pipelines, MCPs, and agent frameworks (Google ADK). * Demonstrated effectiveness with AI coding tools (Devin, Claude Code, GitHub Copilot, Antigravity). * Strong experience with ML frameworks (TensorFlow, PyTorch) and data science libraries. * Proven ability to design and expose robust, scalable APIs for AI services.

- Engineering Excellence: Deep expertise in software engineering best practices, including system design, CI/CD, testing strategies, resiliency, security, and operational stability for AI‑driven platforms.

- Architecture & Data: Strong experience designing API‑first, microservices‑based, and event‑driven systems, including AI‑focused data pipelines and lifecycle management.

- Platforms: Hands‑on experience with Docker and Kubernetes.

- Leadership & Communication: Exceptional ability to articulate complex technical concepts, influence senior stakeholders, and lead high‑impact technical discussions.

- Domain Expertise: Strong understanding of banking and regulated financial environments, with the ability to connect AI capabilities to measurable business outcomes.

Nice to Have

* Advanced data science expertise (statistical modeling, experimentation). * Demonstrated experience mentoring and scaling AI‑first engineering talent in rapidly evolving toolchains.

Experience:

* Progressive software engineering experience with sustained hands‑on contributions. * Advanced level of expertise in Python language * Dedicated experience in AI, LLM‑based systems, and agentic architectures. * Proven success architecting and delivering multiple enterprise‑scale AI solutions into production.

Education: Bachelor’s or Master’s degree in Computer Science, AI, Robotics, or a related quantitative discipline.

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

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

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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.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.

About Machine Learning Engineer jobs in the United Kingdom

Open jobs
338 open Machine Learning Engineer jobs in the United Kingdom, 38 of them posted in the last 7 days. See all Machine Learning Engineer jobs in the United Kingdom
Typical advertised pay
£98,000 – £240,000 a year for the middle half of the 25 job ads from 13 employers that state a salary in British pounds (median £155,000). This is base pay as advertised, not total compensation.
Skills the job ads ask for most
  • Python 81%
  • LLMs 69%
  • AWS 36%
  • RAG 35%
  • CI/CD 30%
  • PyTorch 28%

Share of the 478 newest postings for the role that name each skill. Resume keywords for Machine Learning Engineer jobs

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