Role / Job Title: Prompt Engineer Work Location: London 250 Bishopsgate (on site) The Role A Prompt Engineer in the Data and Analytics domain within banking plays a crucial role in leveraging Generative AI (GenAI) and Large Language Models (LLMs) to extract valuable insights and automate processes efficiently and compliantly. Your Responsibilities Design, develop, and refine prompts to maximize the accuracy and effectiveness of GenAI models.
Utilize techniques like few-shot prompting, chain-of-thought, and RAG (Retrieval Augmented Generation) to improve model performance within banking applications.
Iteratively test and refine prompts based on the evaluation of AI outputs to enhance model performance.
Manage the full prompt lifecycle, ensuring alignment with business needs and technical requirements.
Formulate precise queries to guide AI models in analyzing vast datasets for market trends, risk assessment, and portfolio optimization.
Help generate automated reports, summaries of key financial metrics, revenue/expense forecasts, and risk assessments.
Optimize AI outputs to turn raw data into actionable insights for decision-making.
Your Profile Essential Skills / Knowledge / Experience: Strong understanding of Large Language Models (LLMs), including architectures, capabilities, and limits.
Familiarity with different GenAI model types, such as text generation, summarization, and question answering.
Knowledge of model hallucinations, bias, and context windows.
Mastery of prompting strategies such as zero-shot, few-shot, chain-of-thought (CoT), tree-of-thought (ToT), and self-consistency.
Expertise in Retrieval Augmented Generation (RAG) architecture and implementation to integrate external, up-to-date, and proprietary data sources.
Knowledge of prompt templating, variable injection, and dynamic prompt generation.
Strong SQL skills for querying and extracting data from banking databases.
Proficiency in Python (or similar) for data manipulation, scripting, automation, and integrating with AI APIs.
Familiarity with data structures and data warehousing concepts.
Understanding of API authentication, rate limits, and error handling.
Desirable Skills / Knowledge / Experience: Analytical and critical thinking.
Strong verbal communication skills to collaborate with data scientists, engineers, business stakeholders, and legal teams.
Meticulousness in crafting prompts, as small changes can impact AI output quality and adherence to regulatory requirements.
Ability to work effectively in cross-functional teams (Data Science, ML Engineering, UX, Legal, Business Units).
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