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# Lead Gen AI Data Scientist

- **Company:** Bluevine Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Performance Tuning, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Llamaindex, Generative AI, Agentic-AI, Machine Learning Operations
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8fsz4x5s

## About the Role

At Bluevine, we are building the next generation of AI-powered capabilities that support data-driven decision-making across the company. We are looking for a LeadData Scientist with hands-on experience in Generative AI, Large Language Models, and applied machine learning., * 8+ years of hands-on experience in Data Science, Machine Learning & Applied AI. Strong experience with Generative AI and Large Language Models.

 * Experience building LLM-based applications, AI agents, RAG solutions, or other production-oriented AI systems.
 * Experience with context engineering, model evaluation, fine-tuning, embeddings, or vector databases.
 * Strong proficiency in Python and common data science and machine learning tools.
 * Experience deploying and monitoring AI or machine learning solutions in production.
 * Strong analytical, problem-solving, communication, and collaboration skills.
 * Ability to work independently and translate AI capabilities into practical business solutions.

Nice to Have

 * Experience with LLMOps, model observability, or cloud-based AI services.
 * Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
 * Background in financial services, risk, fraud, or customer analytics.

## Description

* Research and evaluate LLMs and Generative AI techniques for business and data science use cases.
 * Collaborate with technical and cross-functional teams to integrate AI capabilities into existing products and workflows.
 * Share knowledge and support the adoption of Generative AI across the organization.
 * Design experiments to adapt and evaluate foundation models using internal and domain-specific data.
 * Build and productionize LLM-based applications, AI agents, and RAG solutions.
 * Develop prompting, retrieval, and evaluation strategies to improve model quality, reliability, and business impact.
 * Work with embeddings, vector databases, and LLM orchestration frameworks.
 * Apply Generative AI to use cases such as risk modeling, fraud detection, and customer analytics.
 * Monitor and improve the performance, cost, and reliability of AI solutions in production.