Staff Software Engineer (Credit Insights)

• The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers
• We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly
• You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap
• You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions
• Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training
• Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors
• Collaborating closely with Product, Data Science, and Machine Learning partners to develop and scale insights products that enable Credit underwriting use cases
• Mentoring engineers and contributing to a strong, inclusive team culture

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft

• [nice-to-have] Experience working in the credit or lending space
• Strong experience building and scaling backend products
• Strong technical leadership skills, including mentoring peers, leading projects and driving architectural decisions
• Demonstrated success in building and maintaining production systems that serve and support ML models, both in online and offline settings - as well as working closely with data science or ML teams
• Experience collaborating with cross-functional stakeholders and with teams and leaders across the engineering function