Junior Generative AI Application Developer

Overview

Engineer the future of global finance. At Citi, our Tech team helps redefine finance on a global scale. Our network processes trillions of dollars daily across 180+ countries. We deploy advanced AI and build systems that matter, helping shape global markets. Join a team where your work influences economies, your ideas drive innovation, and growth is supported by mentorship, continuous learning, and flexible, potentially hybrid work opportunities.

Learning & Growth

We provide the knowledge and skills you need to succeed. For individuals starting their careers, Citi offers a supportive environment with internal development paths designed to help you build a broad skillset and accelerate your career by gaining exposure to more than one team in Software Development. Our environment helps you discover the best fit for your skills and long-term goals at Citi.

Your Role & Experience

Your time here will involve thriving in an agile software development environment, crafting high-quality, scalable software solutions using cutting-edge technologies, including AI-powered tools. You will translate business requirements into robust code, adhere to stringent quality standards, and provide essential support during testing cycles and post-production deployment. You’ll work to deliver enterprise-level systems that are high quality, scalable, and resilient, leveraging advanced tools for testing and debugging, while learning from senior technologists through design sessions and peer code reviews. You’ll join a cohort of new hires on a shared journey to master Citi’s culture, tools, processes, and the technical proficiencies essential to your success.

Technologies, Tools & Areas of Focus

While technologies may vary across teams and AI tooling is rapidly evolving, developers will gain exposure to a wide range of technologies and tools across all aspects of the SDLC:

• Back-End Microservices Development: Java, Spring Framework
• Mobile Development:
  • iOS: Swift, Xcode, MVC Architecture
  • Android: Android Studio, JavaScript, CSS, AJAX, Java Web Services
• Front-End Web Development: React or Angular, TypeScript, HTML5
• Generative AI & AI Agents: Tools and practices supporting Gen AI development
• Tools: GitHub Copilot with various models, Citi Squad (automated code reviews), Devin.AI (Agentic Code generation), Prompt Engineering, Workflow Design, GenAI Optimization, Stylus Workspaces (In-house Gemini)
• Large Language Models (LLMs): Gemini, OpenAI, Claude, Llama, Local Models
• Frameworks: LangChain, LlamaIndex, Hugging Face
• Orchestration: LangGraph, Multi-Agent Systems
• Development Languages: Java, Python, FastAPI
• Retrieval-Augmented Generation (RAG): PostgreSQL, Vector DBs, Advanced Retrieval
• ML/DL Frameworks: PyTorch, TensorFlow, Fine-tuning
• Deployment: Enterprise DevOps Pipeline, Docker, Monitoring Tooling
• Data Analytics: Splunk, Tableau, and Adobe Analytics to track customer journey adoption and measure business value of delivered products

Key Individual Contributor Exposure

• Gen AI Strategy & Cloud Deployment: Contribute to adopting and deploying Generative AI models and solutions on cloud providers (e.g., AWS), leveraging specialized AI/ML services for scalable inference. Includes advanced AI engineering practices to optimize performance and reliability.
• Engineering Excellence (AI/MLOps): Adhere to Citi's Minimum Development Standards and Minimum Operational Standards, applying MLOps best practices, ethical AI guidelines, and responsible AI development, especially for managing lifecycle of Gen AI agents.
• Architectural Patterns (Gen AI Focus): Explore and apply modern design patterns and frameworks, including Gen AI model architectures (Transformers, GANs), prompt engineering patterns, scalable inference solutions, Microservices, APIs, Spring Core/MVC/Boot/Cloud, and RESTful services. Design and build agentic flows for complex business processes.
• CI/CD & Gen AI Development Tools: Exposure to CI/CD tools (JIRA, Zephyr, GitHub, Harness, Artifactory), MLOps platforms, model versioning, AI-specific testing frameworks, and container orchestration (OpenShift).
• Event Streaming & Messaging (AI Data Pipelines): Work with Kafka, Flink, Solace, or similar systems for real-time data ingestion for Gen AI model training, fine-tuning, and inference.
• Containerization (AI Model Deployment): Hands-on experience with Docker and Kubernetes for scalable deployment of Gen AI models and related microservices.

What You Can Expect Across Teams

• Global Gen AI Exposure: Work on globally scoped Gen AI projects with cross-functional teams, gaining insights into how Gen AI is reshaping finance worldwide.
• Continuous Learning & AI Advancement: Access structured learning paths, mentorship, and development opportunities to strengthen technical prowess in Generative AI, enhance business acumen, and cultivate leadership skills. This includes building agents on Citi’s ARC platform.
• Real Impact with AI: Contribute to real-world projects shaping the future of banking, including AI solutions, intelligent automation, cybersecurity enhancements, and data-driven innovations.

Qualifications & Requirements

• Educational Background: Bachelor’s degree in a technology-related field (e.g., Computer Science, Computer Engineering, Information Technology, MIS) with specialization or strong coursework in Artificial Intelligence, Machine Learning, Data Science, or equivalent hands-on experience.
• Problem-Solving & AI Acumen: Proactive problem-solver who thrives on innovation, leveraging Generative AI to address complex business problems and develop novel solutions.
• Global Mindset: Global outlook with a strong willingness to collaborate across cultures and time zones; understands the global implications of AI development.
• Communication & Leadership: Excellent communication, project management capabilities, leadership potential, keen attention to detail, and ability to work effectively within diverse teams and articulate AI concepts.
• Technical Proficiency (Gen AI): Demonstrated proficiency in Generative AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face), model development, prompt engineering, and AI architecture. Strong experience in AI engineering, particularly in building agentic flows and agents on Citi’s ARC platform is highly valued.
• Collaboration & Adaptability: Collaborative, adaptable, and experienced in agile environments; able to deliver AI solutions in fast-paced settings.

Who We Think Will Be a Great Fit

• Ambitious individuals with a relentless drive to succeed in a fast-paced, dynamic environment.
• Curious about how Generative AI can revolutionize finance and eager to be at the forefront of this transformation.
• Aspiring to grow into a future Gen AI leader, combining a passion for AI with its strategic application in global finance.

Citi is an equal opportunity employer, and qualified candidates will be considered without regard to 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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