Manager Data Science (LLM/RAG/agentic systems)

We are seeking a Manager of Data Science to lead a high-impact team focused on building intelligent systems powered by LLMs and RAG architectures. This role will focus on improving LLM-powered drafting and retrieval solutions through advanced search, embeddings, reranking, evaluation, and production-grade ML components. You’ll drive the strategy, technical execution, and team growth necessary to build next-generation legal assistants, capable of contextual document drafting, and interaction with structured and unstructured data sources. Key Responsibilities:Vision & Strategy:Define the roadmap for applying LLMs and agentic AI to real-world legal drafting.Evangelize and embed AI-driven change across legal product platforms.Translate evolving generative AI capabilities into tangible customer value within the legal domain.Technical & Product Leadership:Architect systems that combine foundation models with RAG pipelines to draft contracts, memos, and pleadings grounded in enterprise knowledge.Guide the development of AI agents that perform multi-step reasoning, cite evidence, retrieve domain-specific content, and produce compliant outputs.Team & Operational Excellence:Mentor and grow a multidisciplinary team of LLM-focused Data Scientists and ML Engineers.Drive cross-functional collaboration with Legal SMEs, Data Engineers, Product Managers, and Design.Establish best practices for evaluation, observability, and responsible use of generative AI. Core Qualifications:ExperiencePrevious people management experience (3+ years) of teams building LLM-based applications, especially in domains requiring rigor and traceability like legal, finance, or compliance.Hands-on experience delivering systems using LangChain, LLM agent frameworks, vector databases, and prompt orchestration pipelines.Strong background in deploying retrieval-augmented generation (RAG) systems for grounded and auditable responses.Demonstrated success in taking LLM-powered applications from prototype to production.Technical ProficiencyProficient with Python and LLM tooling: LangChain, HuggingFace Transformers, OpenAI APIs, and prompt tuning techniques.Familiarity with vector databases (e.g., Solr, Elasticsearch, Qdrant, Weaviate), knowledge graphs, and hybrid retrieval architectures.Working knowledge of containerization (Docker, Kubernetes), CI/CD, and model serving tools (TorchServe, Triton, Ray Serve).Cloud infrastructure experience on AWS, Azure, or GCP.Preferred BackgroundGraduate degree in Computer Science, AI, Machine Learning, or equivalent experience.6 years of post-degree experience, with 3+ years in a data science or applied AI leadership role, with a focus on NLP/LLM systems.Prior experience in legal tech, legal AI, or document-intensive domains is highly desirable.Familiarity with ethical/legal considerations in deploying generative AI in professional settings.