AI Engineer

Introduction

Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together. Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.

Overview

You will partner with business stakeholders to design AI-driven extraction rules that convert unstructured documents into high‑value structured data. You’ll craft and evaluate prompts for LLM-based extraction, maintain a Python codebase that powers workflows, and translate stakeholder needs into repeatable, auditable extraction pipelines.

How you'll make an impact

• Translate business requirements into precise extraction targets, schemas, and quality thresholds.
• Design, test, and iterate prompts for LLM-based extraction; implement evaluation protocols (e.g., accuracy, precision/recall).
• Configure and maintain extraction workflows in Python, including parsing, validation, and post-processing rules.
• Triage and resolve minor code issues; write unit tests and improve logging, monitoring, and error handling.
• Work closely with the GB Data Science team in the US in an onsite-offshore model.
• Partner with business owners to review outputs, prioritize improvements, and manage a backlog in Azure DevOps.

About you

• 0–2 years hands-on experience with an object-oriented language; Python preferred. (Internships, coursework, or projects count.)
• Advanced English Level (B2 conversational level)
• Practical experience crafting prompts for LLMs and evaluating outputs (few-shot prompts, structured output formats, guardrails).
• Ability to read/modify Python scripts, debug minor issues, and write clear, maintainable code.
• Familiarity with version control and basic CI/CD or repeatable execution (e.g., scripts, notebooks, pipelines).
• Strong communication skills: can elicit requirements, clarify edge cases, and document decisions and workflows.
• Working knowledge of handling sensitive data securely and following standardized procedures.

Preferred qualifications:

• An undergraduate degree in Computer Science, Data Science, Information Systems, or equivalent experience.
• Experience with enterprise-scale datasets or high-volume document processing.
• Exposure to Azure services, ideally Azure AI Search/Cognitive Search and Azure OpenAI.