SoFi currently has seven active job listings for AI-related roles. The majority of these positions are in the application stage, accounting for 43% of the openings, with an equal percentage also in the agents stage. Engineering is the most frequent function for these hires. SoFi is actively recruiting for roles that frequently mention tech tags such as model serving, LLM observability, and agent orchestration. Over the last 30 days, SoFi has added six new AI roles, representing a 50% increase compared to the previous 30-day period.
Currently tracking 4 active AI roles, up 29% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $128k–$297k (avg $199k).
SoFi currently has 7 active AI-related roles in our index. The most common open titles are: Finance System Architect Manager, Fraud Model Developer, Senior Manager, Data Science, Senior Staff Software Engineer, AI Accelerated SDLC, Staff Security Detection Engineer, Machine Learning. Most positions are in Engineering.
SoFi's active AI hiring is concentrated in: application (43%), agents (43%), post-training (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
SoFi is hiring AI talent in: United States (7 roles).
Job postings at SoFi most frequently mention: Tool-Using Agents, System Design, Software Engineering, Service Mesh, Agent Research.
In the past 30 days, SoFi has posted 7 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| AI Financial Planning Analyst This role focuses on evaluating and improving the quality of SoFi's AI Coach chat tool by reviewing member interactions, identifying risks, and contributing to enhancements. It requires a blend of financial services expertise and familiarity with AI tools, with a strong emphasis on quality assurance and driving actionable insights for various teams. | Eval Gate | 5 |
| Fraud Model Analyst This role focuses on the governance, oversight, and lifecycle management of third-party fraud models within a fintech company. The Fraud Model Analyst will ensure vendor models are compliant, well-documented, and effectively monitored, partnering with various internal teams (MRM, Legal, Compliance, Fraud Strategy) and external vendors. Responsibilities include managing the model lifecycle, analyzing performance, investigating issues using SQL and Python, supporting integration with internal models, and preparing documentation and audit responses. The role requires experience in fraud, risk analytics, or model governance, with proficiency in SQL and Python, and knowledge of MRM frameworks. |
| 5 |