LLM Consultant

Description

Job Summary: We are seeking an LLM Consultant with experience in LLM-based applications to design, build, and optimize generative AI solutions. Key Highlights: 1. IA Agent Design and Orchestration with RAG and Prompt Engineering 2. Development of Data Pipelines for GenAI and Model Experimentation 3. AI Risk Management and Collaboration with Multidisciplinary Teams **Description:** ---------------- NS Group is recruiting an LLM Consultant with a minimum of 5 years’ experience in LLM-based applications—from conception through production—to perform the following responsibilities: * Design, build, and orchestrate AI agents, implementing techniques such as RAG (Retrieval\-Augmented Generation) and Prompt Engineering. * Develop and validate GenAI-specific data pipelines: ingestion, chunking, embeddings, and re\-ranking strategies. * Experiment with generative models, optimizing performance via advanced prompt engineering and evaluation frameworks (evals) for safety and coherence. * Manage AI-associated risks (bias, hallucinations, privacy), complying with client standards. * Collaborate closely with product, engineering, and design teams to translate business needs into high-impact technical solutions NS is an organization that values both the technological professional profile of its employees and their interest and aptitude in developing new projects. Therefore, we seek individuals who are consistent, eager to evolve, and committed to continuous learning **Requirements:** --------------- 5 years of experience: Skills: * Expert-level proficiency in Python (Pandas, NumPy, Pydantic, Scikit\-learn). * GenAI \& LLMs: Experience in Prompt/Embedding engineering, RAG architectures, and agent design. * Frameworks: Proficiency with frameworks such as LangChain, LangGraph, and libraries like AgentsSDK. * Fundamentals: Solid knowledge of Statistics, Machine Learning, and SQL. * Cloud: Demonstrable experience in cloud environments, primarily AWS. Financial sector and banking domain knowledge is a plus. Work Mode: Hybrid — 2 days per week in Madrid