About this role
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Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
SoFi’s Senior Staff AI Engineer is a hands-on AI engineering role in SoFi’s growing independent risk organization. This is a critical, senior role responsible for setting the technical direction, driving execution, and ensuring the successful delivery of our most complex, production-level AI initiatives. This role will be instrumental in conceptualizing, prototyping and implementing best-in-class AI-based solutions to meet risk management and compliance requirements.
This hands-on role will work closely with the Director of Risk Analytics, and will leverage your deep expertise to solve our hardest problems, mentor the next generation of engineers, and directly connect technical innovation to major business success. This is a crucial role for the independent risk function as we execute our mission to help more members get their money right.
What you’ll do:
• Architecture and Strategy: Define the long-term technical architecture and strategy for our next-generation AI platform, particularly focusing on robust, scalable agentic frameworks and LLM deployment patterns.
• Advanced LLM Orchestration: Architect and standardize the use of graph-based LLM orchestration, leveraging expert-level mastery of LangGraph to solve highly complex, multi-stage reasoning problems at scale.
• Distributed Agent Memory & State: Develop robust, persistent infrastructure for agentic state management, ensuring that long-running agent workflows maintain context and reliability across distributed nodes and regional failovers
• Deep Model Optimization: Pioneer and institutionalize advanced parameter-efficient fine-tuning (PEFT) and compression techniques to maximize model performance and minimize operational costs across the organization.
• Model Serving Infrastructure: Support the development of a unified model serving platform designed to host internally fine-tuned and custom-trained models to ensure high-throughput, low-latency inference across diverse hardware footprints.
• Operational Excellence: Define and enforce high standards for AI operationalization, requiring mastery in designing and deploying comprehensive AI observability solutions and advanced tracing/testing frameworks that guarantee production quality, compliance, and reliability.
• Mentorship: Mentor senior an