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About the Role
SoFi's Senior Staff AI Engineer is a hands-on role within the independent risk organization, responsible for setting technical direction, driving execution, and ensuring the successful delivery of complex, production-level AI initiatives. This role will conceptualize, prototype, and implement AI-based solutions for risk management and compliance, working closely with the Director of Risk Analytics to solve challenging problems, mentor engineers, and connect technical innovation to business success.
Responsibilities
- Define the long-term technical architecture and strategy for the AI platform, focusing on scalable agentic frameworks and LLM deployment patterns.
- Architect and standardize the use of graph-based LLM orchestration using LangGraph for complex reasoning problems.
- Develop persistent infrastructure for agentic state management to maintain context and reliability across distributed nodes.
- Pioneer and institutionalize advanced parameter-efficient fine-tuning (PEFT) and compression techniques to optimize model performance and minimize costs.
- Support the development of a unified model serving platform for custom-trained models, ensuring high-throughput, low-latency inference.
- Define and enforce high standards for AI operationalization, including AI observability solutions and advanced tracing/testing frameworks.
- Mentor senior and junior AI Engineers to elevate overall engineering quality.
- Coordinate with cross-functional teams to distill requirements, define project roadmaps, and ensure timely project deliveries.
- Stay up-to-date with the latest trends in GenAI, LLMs, and NLP, experimenting with new techniques to drive AI innovation.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field (PhD is a plus).
- 8+ years of software development experience.
- 3+ years of hands-on experience developing and deploying production-level AI applications.
- Expert-level experience with LangGraph for LLM application orchestration.
- Expert-level proficiency in developing agentic solutions with a portfolio demonstrating advanced use of planning, memory management, tool integration, and control flow.
- Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and advanced text generation techniques.
- Proven experience implementing parameter-efficient fine-tuning (PEFT) techniques (e.g., LoRA).
- Deep expertise in building or extending inference engines (e.g., vLLM, NVIDIA Triton, or TGI) and managing Kubernetes/GPU orchestration.
- Deep experience designing and institutionalizing AI observability solutions (e.g., LangSmith, Arize, Deepchecks) and advanced tracing/testing methodologies.
- Experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- Expert level Python required.
- React is strongly preferred.
- Experience with large-scale data handling, including unstructured and structured data pipelines, with a preference for Snowflake and DynamoDB.
- Experience developing and integrating AI-powered APIs and microservices architecture into banking applications.
- Experience with vector databases and retrieval-augmented generation (RAG) techniques using systems like Elasticsearch, Pinecone, or FAISS.
- Exceptional ability to communicate complex technical concepts, drive consensus among senior technical leaders, and influence organizational AI strategy.
- Strong analytical and problem-solving skills with attention to detail.
- Strong collaboration skills, with experience working in agile, cross-functional teams.
- Familiarity with regulatory frameworks and ethical considerations in AI within the banking industry (e.g., GDPR, data privacy, model explainability) is a plus.
- Experience in banking or financial services use cases such as conversational AI for customer service, intelligent document processing for loan applications, fraud detection, or risk analysis is a plus.
Skills
- AI
- Machine Learning
- LLM
- LangGraph
- Agentic Solutions
- PEFT
- Inference Engines
- Kubernetes
- GPU Orchestration
- AI Observability
- Tracing
- Testing
- AWS
- Azure
- GCP
- Docker
- Python
- React
- Data Handling
- Snowflake
- DynamoDB
- APIs
- Microservices
- Vector Databases
- RAG
- Elasticsearch
- Pinecone
- FAISS
- GenAI
- NLP
Location
- Remote (excluding Hawaii, Alaska or Puerto Rico)
Work Type
- Full-time
Experience Level
- Senior Staff
- 8+ years software development
- 3+ years hands-on AI application deployment
Education Level
- Bachelor's degree in Computer Science, Data Science, AI, Machine Learning, or related field
- Master's degree in Computer Science, Data Science, AI, Machine Learning, or related field
- PhD is a plus
Benefits
- Comprehensive and competitive benefits
About the Company
- Shape a brighter financial future with us.
- We are a next-generation financial services company and national bank using innovative, mobile-first technology.
- We are at the forefront of an unprecedented transformation in the financial industry.
- Our work has a direct impact on people's lives, guided by our core values.
Equal Opportunity
- SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, gender, gender identity, gender expression, national origin, ancestry, age, 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.
- SoFi offers reasonable accommodations to candidates with physical or mental disabilities.