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Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and in our clients’ best interests. As a financial institution that touches every region of the world and every sector that shapes your daily life, our Enterprise Operations & Technology teams are charged with a mission that rivals any large tech company. Our technology solutions are the foundations of everything we do from keeping the bank safe, managing global resources, and providing the technical tools our workers need to be successful to designing our digital architecture and ensuring our platforms provide a first-class customer experience. We reimagine client and partner experiences to deliver excellence through secure, reliable, and efficient services. Our commitment to diversity includes a workforce that represents the clients we serve from all walks of life, backgrounds, and origins. We foster an environment where the best people want to work. We value and demand respect for others, promote individuals based on merit, and ensure opportunities for personal development are widely available to all. Ideal candidates are innovators with well-rounded backgrounds who bring their authentic selves to work and complement our culture of delivering results with pride. If you are a problem solver who seeks passion in your work, come join us. We’ll enable growth and progress together.
Job Responsibility:
Develop & Prototype: Design, build, and iterate on prototypes for Generative and Agentic AI applications with speed and agility, demonstrating the art of the possible
Implement AI Models: Implement, train, and fine-tune a variety of machine learning and deep learning models to solve complex business problems
Build Robust Systems: Develop and maintain clean, efficient, and scalable code for AI/ML systems, with a focus on production-level quality
Manage Data Pipelines: Engineer and manage sophisticated data handling and preprocessing pipelines to ensure high-quality data for training and inference
Deploy & Operate: Utilize MLOps best practices to deploy AI applications in containerized environments like OpenShift, ensuring robust monitoring, scalability, and reliability
Innovate & Research: Actively monitor and research the latest trends, breakthroughs, and tools in AI/ML. Present findings and lead proof-of-concept projects to integrate new technologies into our stack
Collaborate: Work closely with senior engineers, architects, and product managers in a highly collaborative environment to translate business requirements into technical solutions
Requirements:
2 years in a product development/product management environment
Python Proficiency: Strong and efficient programming skills in Python, including deep familiarity with AI-centric libraries (e.g., NumPy, Pandas, Scikit-learn)
ML/DL Foundation: Solid understanding and practical implementation experience with machine learning algorithms and deep learning architectures (e.g., Transformers, CNNs, RNNs)
Generative AI Experience: Demonstrable understanding of and hands-on experience with Generative AI, Large Language Models (LLMs), and Agentic AI frameworks
Data Expertise: Proven ability in handling and preprocessing large and complex datasets, including data cleaning, feature engineering, and validation
MLOps Awareness: Working experience or strong familiarity with MLOps principles, including containerizing applications using Docker and deploying on platforms like OpenShift or Kubernetes
Problem-Solving: Strong analytical and problem-solving skills with the ability to tackle complex challenges independently
Bachelor’s/University degree or equivalent experience
Core Technical Stack & Expertise: LLMs: Gemini, OpenAI models (GPT series), Copilot, Claude, Llama, and experience with Local Models
Frameworks: LangChain, LlamaIndex, and the Hugging Face ecosystem (Transformers, Datasets, Tokenizers)
Orchestration: LangGraph and conceptual understanding of building Multi-Agent Systems
Development: Building production-ready services using Python, FastAPI, and asynchronous programming patterns
RAG (Retrieval-Augmented Generation): Advanced retrieval techniques using Vector DBs (e.g., Pinecone, Chroma) and PostgreSQL (with pgvector)
ML/DL Platforms: PyTorch and/or TensorFlow for building and fine-tuning models
Deployment & Monitoring: Containerization with Docker, deploying production APIs, and implementing robust monitoring and logging
Applied AI Skills: Advanced Prompt Engineering, AI Workflow Design, and GenAI application optimization for cost, latency, and performance
What we offer:
medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays