Senior Applied AI Full-Stack Engineer - Vice President

What Sets This Role Apart

This is not a conventional engineering role. You are expected to operate as a force multiplier — directing AI agents across multiple workstreams, validating output for production safety, and coaching others to do the same. The measure of success is not lines of code written, but outcomes delivered, quality maintained, and the team's collective capability raised.

Key Responsibilities

• Design and build large‑scale internet/intranet web application platforms on micro‑services architecture, owning decisions across the full stack — from Angular frontends to Java/Spring Boot backends and MongoDB data layer.
• Lead system design at both high and low levels, producing artefacts such as sequence diagrams, class diagrams, and data models, while ensuring security, scalability, and performance are built in from the start.
• Leverage AI coding agents (e.g., Claude Code, Cursor, Devin) for code generation, debugging, and routine tasks; engineer high‑quality context (repository structure, API specs, Jira tickets) to maximize the accuracy and reliability of AI output.
• Critically review, validate, and take ownership of all AI‑generated code ensuring structural integrity, security compliance, and production readiness before anything reaches deployment.
• Integrate agentic workflows into CI/CD pipelines; manage multiple workstreams concurrently through intelligent delegation to AI agents.
• Act as a player/coach within small, co‑located squads — hands‑on in delivery while actively upskilling junior engineers to become effective AI‑first practitioners.
• Apply a strong functional understanding of Corporate Banking to ensure solutions address real business outcomes, not just technical requirements.

Required Skills & Experience

• 6+ years hands‑on experience with Java and Spring Boot for building scalable microservices, and Angular 16+, TypeScript, JavaScript, HTML5, JSON, CSS, Web Sockets, and Ajax.
• Proven experience designing large‑scale internet/intranet platforms using micro‑services architecture.
• Strong fundamentals in systems analysis, design patterns, and SDLC, including unit testing and CI/CD practices.
• Ability to produce high‑level and low‑level design artefacts (sequence diagrams, class diagrams).
• Proficiency in Python for scripting, automation, or AI‑adjacent tooling.
• Hands‑on experience with MongoDB; solid understanding of modern database design and data modelling.
• Good understanding of message brokers; Kafka experience highly desirable.
• Demonstrated, hands‑on proficiency with AI coding tools (e.g., Claude Code, Cursor, GitHub Copilot, or equivalent).
• Spec‑driven development – ability to write structured prompts, engineer context, and decompose complex problems into tasks suitable for AI agent delegation.
• Proven ability to identify and resolve AI failure modes before they reach production.
• Strong experience with GitHub for source control and Jira for project management.
• Proven experience in Agile/Scrum delivery.

Domain

• Functional understanding of Corporate Banking — able to articulate why their work matters, not just how it is built.

Education

• Bachelor’s degree/University degree in Engineering, Finance, or equivalent experience.

Equal Opportunity Statement

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.