Data Prompt Engineer

A global financial technology organization is seeking a hands-on Data Prompt Engineer to support the development of an emerging data and ontology platform. This position combines AI-driven software engineering, agent workflow design, systems architecture, and hands-on user interface testing.

The ideal candidate will use Claude and AI coding agents to build and improve application functionality while personally validating how the software behaves. Success requires strong engineering judgment, practical troubleshooting skills, and the ability to work independently across multiple aspects of software delivery.

Responsibilities

• Design Claude-centered prompts, AI agent workflows, and plugin/tool integrations.
• Guide AI agents in creating, modifying, and refining application interfaces.
• Personally inspect and test generated UI functionality to identify defects and edge cases.
• Design reliable application behavior involving state management, recovery, and synchronization.
• Troubleshoot problems and refine agent instructions, software behavior, or architecture.
• Collaborate with backend and data engineering colleagues to connect interfaces with data services and models.
• Translate evolving requirements into practical engineering decisions.
• Contribute across development, design, testing, and validation as the platform progresses toward an MVP.

Role Requirements

• 4+ years of software, systems, or related engineering experience.
• Strong recent experience using Claude and AI coding agents in hands-on software development.
• Practical knowledge of prompt architecture, agent workflows, and tool integrations.
• Strong systems design, problem-solving, and troubleshooting capabilities.
• Experience with application reliability, state management, or distributed system behavior.
• Ability to personally test, evaluate, and refine AI-generated application interfaces.
• Familiarity with APIs, backend systems, and data-related application concepts.
• Comfortable working independently in a flexible engineering environment.

Nice to Have

• Systems architecture or backend software engineering background.
• Experience on smaller engineering teams with broad responsibilities.
• Exposure to ontologies, knowledge graphs, or data integration.
• Familiarity with SQL, data models, or modern data platform technologies.
• Financial technology or other data-intensive industry experience.