Sean Fortney

About Sean Fortney

Graduated from the University of Michigan with a B.S. in Computer Science and Cognitive Science — two fields that together push me to think about both the technical and human sides of building software. I have around 3 years of experience at Moody’s, primarily on Risk Modeler 2.0, working on testing automation, debugging, and engineering process improvements on a large-scale financial platform.I also contributed to Agent Mando, an internal agentic AI project focused on bringing LLM-driven automation into production environments — working across tooling, integrations, and deployment workflows.I’m comfortable in Java, Python, PostgreSQL, and SQL, and I gravitate toward roles where I can work close to the full stack, ship features end-to-end, and collaborate closely with other engineers to deliver real

Experience

1. Software Engineer

   Moody's Analytics

   Aug 2024 — Present · New York, NY, US

   Leading end-to-end development of Agent Mando, an AI-driven automation agent — owning requirements discovery, stakeholder alignment, workflow design, and iterative refinement through weekly live demos.∙ Automating recurring workflows for cross-functional PM teams, delivering 4 hours of reclaimed capacity per PM per week — quantifying and communicating ROI to business stakeholders.∙ Diagnosing and refactoring a legacy R data pipeline — migrating it to Python to improve maintainability — enabling accurate tracking of Generative AI usage via Power BI dashboards.∙ Delivering weekly executive-facing briefings to platform leads and Salesforce CPQ / FinancialForce stakeholders, translating technical timelines, risks, and dependencies into clear business narratives.∙ Facilitating cross-functional Scrum ceremonies across Salesforce CPQ and FinancialForce teams, aligning technical and business stakeholders on release priorities, blockers, and go-live readiness.∙ Serving as the technical-to-business bridge between sales operations, finance, and engineering — translating complex quoting and billing workflows into actionable requirements.∙ Partnering with Product, QE, and engineering to validate that new CPQ/FinancialForce features meet go-to-market requirements — connecting technical teams to business outcomes.∙ Enhancing Risk Modeler 2.0 features with a focus on usability and accuracy for financial analysts — balancing technical implementation with deep understanding of end-user workflows.∙ Building and maintaining automated test and deployment pipelines (Java, Maven, PostgreSQL) for Risk Modeler 2.0, improving release cadence and platform stability.∙ Investigating production issues through log analysis and SQL forensics, resolving data inconsistencies that improve analyst trust in financial model outputs — communicating findings to both technical and non-technical stakeholders.

Education

• University of Michigan

  Bachelor of Science - BS, Computer Science and Cognitive Science