Lead Applied AI Engineer - Banking Technology, Senior Vice President

Citi; United Kingdom; On-site; GBP 130,000 - 190,000; Full time

Job summary

Citi is seeking an AI-first Lead AI Engineer to architect and deliver enterprise-scale AI solutions across banking domains. You will lead hands-on development, define agentic architectures, and drive adoption of LLMs and AI platforms while mentoring engineers.

You will collaborate with technology and business teams to ensure robust APIs, secure, scalable AI services, and measurable business impact in regulated environments.

Qualifications

• Proven hands-on expertise in Python/Java and modern web tech.
• Deep knowledge of AI fundamentals, LLMs, and multi-agent systems.
• Experience with AI platforms (OpenAI, Anthropic, Google) and agent frameworks.

Responsibilities

• Lead design, implementation, and deployment of enterprise AI solutions.
• Architect agent-based systems with multiple LLM providers.
• Mentor engineers and drive AI-first culture across teams.

Skills

Python

Java

JavaScript/TypeScript

LLM platforms

Agentic AI

API Design

Docker

Kubernetes

TensorFlow

PyTorch

AI Tooling

Education

Bachelor's or Master's in Computer Science, AI, Robotics

Tools

Docker

Kubernetes

GitHub Copilot

Job description

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.

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.

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