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The AI/Full Stack Tech Lead role is a strategic professional technical specialist with deep domain expertise in Securities-Based Lending (SBL) to join our SBL program, a key part of the OMAI Initiative. The ideal candidate's primary strength will be their comprehensive understanding of the SBL lifecycle, from underwriting and legal documentation to collateral management. This expertise will help with design and implementation of Generative AI solutions, translating the strategic AI roadmap into functional, production-ready code. This role acts as a crucial bridge between the SBL Engineering team and SBL business partners, requiring frequent, direct interaction with specialists in SBL Business, Credit Risk, Legal, and Operations. The goal is to leverage technology to solve complex challenges and drive transformation across our global SBL operations.
Job Responsibility:
Hands-on development and coding of SBL solutions that transform the SBL lifecycle
Writing production-quality code for component-level development of Agentic AI systems, interaction 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
Implementing the data pipelines for these models
Design and build solutions to automate the analysis, extraction, and verification of information from complex legal documents and integrate with DocuSign to significantly reduce the documentation lifecycle
Implement and maintain the data infrastructure required for SBL solutions, demonstrating proficiency with both relational and NoSQL databases
Design and implement robust APIs and data feeds for integrating the SBL platform with critical internal and external systems
Work closely with Credit Risk, Legal, and Compliance partners to ensure the SBL platform accurately implements lending policies and adheres to regulatory requirements
Collaborate with Technology and Business Information Security offices to embed security best practices into the system architecture
Investigate and resolve complex technical issues related to the SBL platform
Practical application of the modern Generative AI stack to build and test predictive models that identify SBL client opportunities and potential risks
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 all SBL AI systems
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.
Familiarity is desirable 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
Bachelor’s degree/University degree or equivalent experience
Master’s degree preferred
Nice to have:
Master’s degree
Experience within a Wealth Management, Private Banking, or Credit technology environment
Familiarity is desirable with ML/DevOps practices (monitoring, troubleshooting, CI/CD for models)
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
discretionary and formulaic incentive and retention awards