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The Citi Innovation Lab is a leader in creating new ideas, innovative technology solutions, and ground-breaking innovations for Citi's global banking business. We're part of a global network of innovation centers, and our mission is to create competitive advantage for our clients by providing innovative technological solutions.
Job Responsibility:
Develop and implement enterprise scale cutting edge models such as visual document understanding and text2code
Implement and Optimize vector-based retrieval systems for RAG by covering embedding models, ANN indexing, hybrid search, and re-ranking
Implement autonomous AI agents to implement adaptive, error resistant data extraction, and content validation tasks
Develop and deploy enterprise software applications using state of the art practices, such as micro services, modular code, as well as proficiency in writing unit and integration tests to ensure the accuracy and reliability of the AI applications
Ensure data privacy and security in all AI-driven processes, adhering to OWASP guidelines and Citi’s stringent authentication and authorization policies
Collaborate with cross-functional teams to integrate AI solutions into existing workflows
Document the development process and create comprehensive technical specifications
Manage and maintain AI applications, ensuring best practices in model management and versioning
Deploy resulting AI applications using industrial strength framework and processes, including Kubernetes and OpenShift for scalable and efficient operations on-premises
Ability to research and develop and utilize transformer-based models for enhanced application performance
Requirements:
Hands-on experience with transformer-based models and their applications
Strong understanding of LLM, LLM model selection, benchmarking, and optimization
Experience with RAG systems and vector databases
Proficiency in developing and deploying AI agents
Knowledge of open-source models and methods, including benchmarks for evaluating AI performance
Knowledge of security risks and mitigation strategies for autonomous AI agents, including OWASP guidelines
Proficiency in Python and experience with libraries such as Pandas, Tabula, and TensorFlow/PyTorch
Strong problem-solving skills and attention to detail
Excellent communication and documentation skills
Nice to have:
Familiarity with regulatory requirements and compliance in AI applications
Experience with financial data analysis and extraction
Experience with unit testing and integration testing frameworks
Experience with Kubernetes and OpenShift for deploying AI applications on-premises
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