Position Overview
We are seeking energetic AI Design Engineers with 1-3 years of experience to help build, scale, and integrate the next generation of AI-powered developer tools, design systems, and data infrastructure.
In this role, you will be part of an agile engineering team using modern programming stacks and AI-assisted development tools to build high-performance backend services, interactive user workflows, and automated quality verification pipelines.
Our team is building an advanced design agent and Model Context Protocol (MCP) server that provides an AI-powered intelligence layer for enterprise development workflows. This platform grounds automated design decisions in standardized UI/UX guidelines and design system practices, ensuring AI-generated interfaces strictly adhere to established components, accessibility standards, content rules, and brand guidelines with consistent quality across web and mobile platforms.
Core Responsibilities (All Tracks)
Regardless of your primary track, as an AI Design Engineer your responsibilities will include:
- Feature Implementation: Write clean, modular, and well-tested code in modern programming languages (e.g. TypeScript, Python).
- AI-Assisted Engineering: Actively leverage modern AI coding assistants (e.g. GitHub Copilot) to accelerate development while applying strong Computer Science principles to ensure code correctness, security, and performance.
- Agile Collaboration: Participate in agile sprint ceremonies, write unit and integration tests, and collaborate with product designers and senior engineers across business lines.
- Enterprise Standards: Ensure all deliverables comply with enterprise security, data governance, and architectural standards.
Additional Focus Tracks Responsibilities
Candidates will align with and contribute to one (or more) of our core engineering focus tracks:
Track 1: Backend Systems & Data Scalability
- High-Performance Data Architecture: Design and optimize Postgres relational and JSON schemas, writing complex queries, indexes, and transactional boundaries to manage multi-dimensional design rule cascades.
- Low-Latency Caching & Scalability: Implement distributed caching layers and invalidation mechanisms to guarantee low-latency data access under high concurrency.
- Protocol & API Engineering: Build robust, streaming REST and Model Context Protocol (MCP) server endpoints to serve real-time design intelligence and tokens to connected developer tools.
- Enterprise Security & Auth: Implement secure token validation, role-based access control (RBAC), and payload sanitization across all data pipelines.
Track 2: Fullstack & User Workflow Integration
- Web Platform Development: Architect performant, responsive web applications and dashboards using React and modern TypeScript, managing complex client-side state and token visualization.
- Figma Integration: Develop event-driven client features for our in-house Figma integrations, handling asynchronous canvas synchronization and bidirectional data serialization between design tools and backend servers.
- Automated Code & Component Parsing: Write automated scripts to programmatically inspect modern design system component libraries, extracting property schemas and design tokens into structured MCP contracts.
- Intelligent Code Adaptation: Develop surgical code-modification routines that allow AI agents to safely parse, update, and integrate new designs into existing application codebases without introducing syntax errors or breaking custom logic.
Track 3: Quality, Reliability & Verification Systems
- Automated AI Verification Harnesses: Design and maintain automated testing engines and regression harnesses in Python or TypeScript to continuously evaluate the quality, compile rate, and accuracy of AI-generated code across web and mobile platforms.
- Systematic Scenario Benchmarking: Maintain a comprehensive suite of standardized baseline test scenarios, systematically tracking compile success rates, design token compliance percentages, and response latency across releases.
- Automated Compliance & Linters: Build automated linters that mathematically verify WCAG 2.1 AA accessibility (color contrast math, DOM focus states) and structural schema validity across all generated outputs.
- CI/CD Quality Gates: Integrate automated verification suites into build and deployment pipelines to catch regressions, token drift, and syntax anomalies before features reach production teams.
Qualifications & Skill Requirements
Basic Qualifications:
- Education: Bachelor’s degree in Computer Science, Software Engineering, Human-Computer Interaction, or a related technical field.
- Experience: 1-3 years of professional software development experience (or equivalent co-op, internship, or open-source project portfolio).
- Programming Skills: Strong proficiency in modern languages: TypeScript/JavaScript, Python, SQL, Swift, or Kotlin
- Foundational CS Knowledge: Solid grasp of core data structures, RESTful APIs, and relational database fundamentals.
- Tooling & AI Fluency: Hands-on experience with Git version control and enthusiasm for using AI-assisted coding tools (e.g. GitHub Copilot, Devin AI) to maximize productivity.
Preferred Skills:
- Familiarity with design systems concepts (e.g., design tokens, component architecture, style dictionaries, or Storybook).
- Working familiarity with Figma as a user or developer (e.g., inspecting designs, Auto-Layout concepts, or exploring Figma APIs).
- Experience with Postgres, SQL indexing, caching strategies, or building low-latency REST/MCP microservices.
- Exposure to native mobile UI development (e.g., Swift / SwiftUI for iOS or Kotlin for Android) and mobile design token patterns.
- Experience with automated testing frameworks (e.g. Playwright, PyTest) and CI/CD quality pipelines.
- Familiarity with web accessibility standards (WCAG 2.1 AA, color contrast math, ARIA attributes, semantic HTML).
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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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Primary Location Full Time Salary Range:
$94,300.00 - $141,500.00
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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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Automated Processing and AI
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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This job opening is for an existing job vacancy.
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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.
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View Citi’s EEO Policy Statement and the Know Your Rights poster.
