Applied AI Data Scientist
Core
Design, prototype, and evaluate agentic AI and LLM-powered solutions for legal research, drafting, and decision-making workflows.
Role type
Senior Applied AI Data Scientist (Agentic AI & LLM Evaluation)
Builds
Production-oriented agentic AI systems, evaluation harnesses, and legal-use capabilities using LLMs, RAG, and multi-step reasoning.
Domain
Legal Technology / Enterprise SaaS / Regulated Industries
Deliverable
production ML models | product features
Required skills
Statistics and experimental design, hypothesis testing, causal inference, Python (pandas, NumPy, scikit-learn), SQL, LLM methods (prompting, RAG, embeddings, structured generation), full modeling lifecycle management, AWS/Azure/GCP, agentic workflow design, error analysis, benchmark development.
Preferred skills
Legal technology domain expertise, agentic workflows with tool-calling, retrieval and ranking optimization, knowledge graph integration, human-in-the-loop evaluation, AI guardrails, fine-tuning, open-source contributions.
Technologies
LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, Google ADK, AWS, Azure, GCP
Responsibilities
Translate ambiguous customer pain points into measurable problems for AI/ML teams. Design and run experiments to validate emerging AI techniques like LLMs and agent patterns. Develop and iterate on LLM-powered solutions including prompt engineering and retrieval strategies. Design and build evaluation harnesses for accuracy, hallucination detection, and trajectory quality in multi-step agents. Contribute production-oriented code and collaborate with engineers to harden prototypes. Partner with legal SMEs and stakeholders to integrate evaluation and monitoring into production applications.
Seniority
Senior, hands-on IC