About The Position

Citi, a leading global bank with a vast customer base and operations in over 160 countries, is seeking an AI/Full Stack Java Tech Lead with deep expertise in Securities-Based Lending (SBL) to join its SBL program, a key component of the OMAI Initiative. This role is crucial for designing and implementing Generative AI solutions, translating the AI roadmap into production-ready code. The position requires a comprehensive understanding of the SBL lifecycle, from underwriting and legal documentation to collateral management. The Tech Lead will act as a bridge between the SBL Engineering team and business partners, collaborating with specialists in SBL Business, Credit Risk, Legal, and Operations to leverage technology for solving complex challenges and driving transformation in global SBL operations. Citi is committed to diversity and fostering an environment where innovation, respect, and personal development are paramount.

Requirements

  • 6-10 years of relevant experience in Application Development.
  • Deep, demonstrable knowledge of the Securities Based Lending (SBL) lifecycle, including loan origination, underwriting, real-time collateral monitoring, and risk management.
  • Knowledge of legal documents templates as part of the SBL lifecycle.
  • Proficiency in deploying applications using Docker, Kubernetes, and OpenShift.
  • Expertise in designing and implementing distributed systems using JAVA, Microservices, with a strong focus on system integration, APIs (including AI based API usage), and data-intensive applications.
  • Experience using AI tools.
  • Experience within a Wealth Management, Private Banking, or Credit technology environment.
  • Knowledge of financial instruments commonly used as collateral (e.g., equities, fixed income, mutual funds) and their valuation principles.
  • Familiarity with lending regulations (e.g., Regulation U) and key risk management concepts (e.g., Loan-to-Value ratios, concentration risk).
  • Proven experience as a senior technical analyst/developer on large-scale, complex financial technology projects.
  • Strong data engineering skills with experience with both relational and NoSQL databases.
  • A strong understanding of implementing secure communication protocols like TLS and token-based authentication (JWT) etc.
  • Bachelor’s degree/University degree or equivalent experience.

Nice To Haves

  • Master’s degree preferred.
  • Familiarity with ML/DevOps practices (monitoring, troubleshooting, CI/CD for models).
  • Excellent communication skills with the ability to translate complex SBL concepts and technical details between business and technology teams.

Responsibilities

  • Hands-on development and coding of SBL solutions to transform the SBL lifecycle.
  • Writing production-quality code for component-level development of Agentic AI systems.
  • Interacting with internal SBL APIs for loan origination, collateral management, and risk assessment.
  • Leveraging the Long Context Advantage to automate and augment the analysis of complex client portfolios and credit agreements for SBL underwriting, including implementing data pipelines for these models.
  • Designing and building solutions to automate the analysis, extraction, and verification of information from complex legal documents (e.g., credit agreements, term sheets, collateral pledges) and integrating with DocuSign.
  • Implementing and maintaining the data infrastructure required for SBL solutions, using both relational and NoSQL databases.
  • Designing and implementing robust APIs and data feeds for integrating the SBL platform with critical internal and external systems (market data providers, risk engines, credit adjudication platforms, downstream loan product processors).
  • Collaborating with Credit Risk, Legal, and Compliance partners to ensure the SBL platform accurately implements lending policies and adheres to regulatory requirements (e.g., Regulation U).
  • Working with Technology and Business Information Security offices to embed security best practices into the system architecture.
  • Investigating and resolving complex technical issues related to the SBL platform, including data discrepancies and performance bottlenecks.
  • Applying the modern Generative AI stack to build and test predictive models for identifying SBL client opportunities and potential risks, requiring strong data engineering and data cleansing skills.
  • Deploying AI models and applications into production on OpenShift using Docker and Kubernetes.
  • Contributing to the team's ML/DevOps practices by implementing robust monitoring, logging, and troubleshooting solutions for SBL AI systems.

Benefits

  • 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.

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What This Job Offers

Job Type

Full-time

Career Level

Senior

Number of Employees

5,001-10,000 employees

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