What we are looking forThread Bank is hiring a Quantitative AI Engineer who works at the intersection of quantitative modeling, software engineering, and applied artificial intelligence. This role owns the models behind risk, liquidity, and fraud decisions; builds and maintains the internal AI systems the bank depends on; provides quantitative advisory support across business lines; and serves as the bank's subject matter expert on AI coding agents. This is an in-person position in Nashville, Tennessee, reporting to the AI Product and Innovation Lead under the broader direction of the Head of Digital Strategy, with direct exposure to senior leaders across Finance, Treasury, Enterprise Risk Management, Financial Crimes Compliance, Embedded Banking, and the data platform teams.
What you'll doQuantitative modeling and validation
- Develop and validate credit risk, liquidity, and fraud models, including backtesting against actual quarterly outcomes and documenting assumptions
- Run outcomes analysis comparing predicted loss distributions and liquidity forecasts to realized results
- Keep enterprise risk models current by incorporating realized loss events throughout the year
- Calibrate the cash management forecasting tool in partnership with Finance
AI systems engineering
- Design, build, and maintain internal AI tooling from prototype through production
- Take the financial crimes analytics platform to full production and develop subsequent internal systems
- Own ongoing maintenance and monitoring of live systems, including the fintech onboarding portal, voice agent, financial crimes analytics platform, and enterprise risk models
- Write, evaluate, and keep production AI software running
Quantitative advisory
- Provide quantitative modeling support across fraud, enterprise risk management, treasury, account analytics, and data teams
- Build and maintain Power BI reporting relied on by the Chief Financial Officer and Treasury, including account monitoring and deposit decay analysis
- Translate business questions into defensible quantitative outputs and communicate findings to senior leaders without jargon AI coding agent subject matter expert
- Set standards for how teams use AI coding agents, including project setup, context and instruction files, agent guardrails, testing, code review, and documentation
- Run enablement sessions, unblock teams, and raise quality standards so that agent-assisted work meets the same bar as all other shipped software
- Remain current on the AI coding agent landscape and advise on tooling decisions across the bank
Qualifications- Nashville office-based position, Monday through Friday
- Bachelor's or master's degree in a quantitative discipline, including statistics, mathematics, economics, finance, engineering, or computer science, or equivalent hands-on experience
- Applied quantitative modeling experience, including building, validating, and backtesting models, documenting assumptions, and quantifying uncertainty
- Strong command of Python and SQL, with fluency in JSON and other structured data formats and comfort reading API documentation
- Demonstrated proficiency using AI coding agents as primary development tools, with the ability to drive them to working software, validate results, and iterate quickly
- Ability to ship production AI systems end to end, covering data access, model or agent logic, evaluation, logging, monitoring, alerting, and escalation paths
- Demonstrated ability to convert ambiguous business questions into clear technical specifications, requirements, and documented outputs
- Applied knowledge of AI quality and governance practices, including confidence thresholds, human-in-the-loop review, sampling, audit trails, and rollback, built in partnership with compliance and risk teams
- Demonstrated ability to quantify business impact with clear assumptions and communicate results to senior leadership without technical jargon
- Track record of independently taking projects from concept through working, documented, and adopted production output.
- Model risk management experience under SR 11-7 or a comparable validation framework
- Hands-on work in credit loss modeling, liquidity forecasting, deposit behavior and decay analysis, or fraud and anomaly detection
- Experience building agentic AI systems, including tool use, retrieval, evaluation harnesses, and orchestration
- Proficiency in Power BI or a comparable business intelligence platform, plus solid Excel modeling skills
- Exposure to regulated environments and banking regulation, including BSA/AML, fair lending, and consumer compliance
- Familiarity with responsible AI practices, model documentation standards, and large language model evaluation
- Comfort with product practices such as requirements, user stories, and acceptance criteria
