Staff Software Engineer, AI - Member Growth
at SoFi
CA - San Francisco, WA - Seattle
Employee Applicant Privacy Notice
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
We are seeking a Staff Software Engineer, AI to join the Member Growth organization with the mission of bringing the value of AI to SoFi Members. This role will be pivotal in supporting our members’ financial journeys through advanced personalization and AI-driven solutions, and lead the development of internal frameworks, tools, and applications that bring cutting-edge capabilities to our marketing, communications, and measurement systems.
Our goal is to help members navigate their path to financial independence by providing the specific tools, resources, and guidance they need to succeed. We aim to be a trusted partner in their financial lives, delivering timely, tailored insights that build long-term confidence. Achieving this requires a thoughtful, highly personalized approach to every user’s unique financial needs.
The ideal candidate possesses a deep understanding of Artificial Intelligence (AI) and Machine Learning (ML) systems, paired with a passion for building next-generation products. At SoFi, we pride ourselves on the seamless collaboration between Product, Design, and Engineering; as such, you will be involved in the entire product lifecycle—from initial ideation to deployment and iterative evolution. We are committed to a philosophy of continuous learning, and we expect you to be equally dedicated to your own professional growth and the mentorship of your fellow team members.
What you’ll do
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Drive technical architecture, design decisions and cross-functional discussions for AI and ML-based solutions
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Deliver highly available and scalable services in a production environment
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Lead the design, development and testing of systems
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Lead code and system design reviews
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Help translate product requirements into user stories and technical solutions
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Mentor other engineers, support the technical culture, and help grow the team
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Generate ideas for new initiatives and technologies
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Communicate with product managers, data scientists, data engineers, and other software developers
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Consistently demonstrate extremely high levels of technical knowledge, ingenuity, and creativity
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Develop and apply advanced technologies, engineering principles, theories, and concepts
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Take initiative and produce timely results in a fast-paced and sometimes ambiguous environment
What you’ll need
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Bachelor’s Degree in Computer Science or related field, or equivalent experience
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8+ years programming experience on a modern stack with expertise in Python
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Experience working with new technologies in the AI stack, such as building Agents, creating MCP servers, fine tuning models, prompt engineering, and performance evaluation
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Experience working with applications that leverage Large Language Models (LLMs), such as integrating LLMs, designing prompts, or exploring their practical applications
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Our core stack is Java/ Kotlin/ Spring/ AWS/ Snowflake, and we run on Kubernetes in a cloud-native service oriented architecture. You should be comfortable developing using some or all of these technologies
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You should have worked on a SOA or microservice-based application
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Strong sense of ownership; driving a project from inception to completion
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Pragmatic approach towards handling tech debt versus shipping new features
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Experience working in a collaborative coding environment, refining designs together, working through code reviews and managing pull requests
