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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:
We are seeking a highly experienced AI Automation Lead with 8+ years of engineering experience to bridge the gap between sophisticated data ecosystems and high-performance user applications. This role is responsible for architecting and delivering our multi-agent AI strategy—moving beyond simple chatbot implementations to autonomous, stateful workflows that solve complex, real-world business problems.
This individual operates as a true full-stack product engineer, equally comfortable working across frontend, backend, data orchestration, and AI systems. You will define the technical vision for AI-driven automation, ensuring solutions are scalable, production-grade, and highly available.
What you’ll do:
AI Architecture & Agentic Workflows
- Design and implement multi-agent AI workflows that enable coordinated task execution across systems (e.g., fraud detection, risk assessment, financial modeling)
- Build human-in-the-loop systems that allow users to monitor and intervene in automated processes
- Integrate Snowflake Cortex for in-database AI workloads, including LLM functions, vector search, and ML processing
Full-Stack Engineering
- Develop complex, data-rich user interfaces using React to visualize and control AI workflows
- Build scalable backend services in Python with a focus on performance, concurrency, and clean API design
- Orchestrate workflows and automation pipelines using Apache Airflow
Data & Infrastructure Strategy
- Leverage Snowflake and dbt to ensure clean, governed, and high-performance data pipelines
- Maintain infrastructure as code and CI/CD pipelines to enable reliable and rapid deployments
- Optimize performance and cost of LLM usage and internal AI systems
Technical Leadership
- Lead architectural decisions and set engineering standards across the team
- Conduct code reviews, mentor engineers, and promote a culture of ownership
- Partner with Product to translate business problems into scalable automation solutions
What you’ll need:
- 8+ years of professional software engineering experience
- Strong expertise in React with the ability to build complex, stateful UIs from scratch
- Deep expertise in Python, including async programming and AI/ML frameworks
- Experience building multi-agent systems or complex AI workflows (e.g., LangGraph, CrewAI, AutoGen, or similar)
- Hands-on experience with Snowflake, including data modeling and AI integrations
- Strong experience with Apache Airflow for workflow orchestration
- Working knowledge of CI/CD pipelines and containerization (Docker, Kubernetes)
- Proven ability to lead technical design and own end-to-end system delivery
Nice to have:
- Experience with Snowflake Cortex or in-database AI processing
- Experience fine-tuning or deploying custom ML models
- Background in fintech, risk, fraud, or financial systems
- Experience migrating manual processes into automated AI-driven systems
- Strong system design experience in distributed, production environments
The profile we’re looking for:
You are a full-stack AI systems architect who thrives on building end-to-end solutions—not just components. You move beyond traditional CRUD applications and focus on delivering intelligent, automated systems that solve meaningful business problems.
You take ownership of both the system and the user experience, ensuring that AI capabilities are not only powerful but usable and scalable. You can take an ambiguous goal—like automating a fraud review process—and turn it into a fully functional, multi-agent system with a robust user interface in a matter of weeks.
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our **Benefits at SoFi **page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.