4 hours ago
Responsibilities
- Define long-term technical architecture and strategy for a scalable AI platform.
- Architect graph-based LLM orchestration with LangGraph for complex, stateful, multi-stage reasoning workflows.
- Develop persistent agent memory and state infrastructure supporting distributed nodes and regional failovers.
- Implement parameter-efficient fine-tuning and model compression techniques to optimize model performance and cost.
- Support a unified model-serving platform for internally fine-tuned and custom-trained models.
- Design and enforce AI operationalization standards, including observability, tracing, testing, compliance, and reliability practices.
- Mentor senior and junior AI engineers and improve overall engineering quality.
- Coordinate with cross-functional teams to define requirements, roadmaps, and delivery plans.
- Evaluate emerging GenAI, LLM, and NLP techniques and tools for banking-sector applications.
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, including 3+ years developing and deploying production AI applications used by customers or internal stakeholders.
- Expert-level experience with LangGraph and sophisticated agentic solutions involving planning, memory, tools, and control flow.
- Deep understanding of LLM architectures, prompt engineering, RAG, and advanced text generation.
- Experience implementing PEFT techniques such as LoRA.
- Deep expertise building or extending inference engines such as vLLM, NVIDIA Triton, or TGI, and managing Kubernetes/GPU orchestration.
- Experience designing AI observability solutions using tools such as LangSmith, Arize, or Deepchecks.
- Experience with AWS, Azure, or GCP and containerization technologies including Docker and Kubernetes.
- Expert-level Python proficiency; React experience is strongly preferred.
- Experience with large-scale structured and unstructured data pipelines, preferably using Snowflake and DynamoDB.
- Experience developing AI-powered APIs and microservices for banking applications.
- Experience with vector databases and RAG using Elasticsearch, Pinecone, or FAISS.
- Strong communication, analytical, problem-solving, collaboration, and organizational influence skills.
- Familiarity with AI regulatory and ethical considerations or banking use cases such as customer-service conversational AI, loan-document processing, fraud detection, or risk analysis is desirable.
Benefits
- SoFi provides comprehensive and competitive benefits; details are available on its Benefits at SoFi page.
- Remote work cannot be accommodated from Hawaii, Alaska, or Puerto Rico.
- The posting includes equal employment opportunity, reasonable accommodation, and fair-chance hiring commitments.
Tech Stack
Categories
About SoFi
SoFi provides consumer banking, lending, and investing products, including student-loan refinancing, personal loans, mortgages, checking and savings, a credit card, and brokerage. It earns interest and fee revenue across SoFi Bank, N.A., and related subsidiaries, serving U.S. consumers via a mobile app. Founded in 2011 and headquartered in San Francisco, SoFi Technologies is publicly traded on Nasdaq under the ticker SOFI.