AI Engineer (Python)

TL;DR

AI Engineer (Python/LLM): Building and optimizing AI-powered consulting tools for scalable delivery with an accent on data mapping, workflow automation, and RAG. Focus on developing deployable web apps, APIs, and agent integrations to reduce manual effort in client engagements.

Location: Copenhagen, Denmark

Company

hirify.global (part of Deutsche Börse) provides investment management software and consulting services to global financial institutions.

What you will do

• Design and build AI-powered tools for data mapping, validation, and documentation generation.
• Develop deployable web applications, APIs, and agent integrations as your skills evolve.
• Implement prompting strategies, Retrieval-Augmented Generation (RAG), and evaluation frameworks.
• Research emerging AI models, tools, and frameworks to evaluate their practical fit for consulting.
• Collaborate with the wider internal AI community to share reusable components and lessons learned.
• Translate complex consultant problems into stable, reusable engineering solutions.

Requirements

• Must be based in Copenhagen
• Recent or final-year BSc or MSc in Computer Science, Software Engineering, or a related field.
• Solid foundation in Python and experience building/consuming REST APIs.
• Exposure to web development using React/TypeScript or Python/Node.
• Familiarity with Git, collaborative workflows, and cloud platforms (Azure or AWS).
• Hands-on exposure to developing AI solutions, prompt engineering, and RAG approaches.

Nice to have

• Experience building and deploying full-stack web applications end-to-end.
• Knowledge of Agentic AI and interoperability protocols like MCP or A2A.
• Experience with Docker, CI/CD, and relational or vector databases (e.g., PostgreSQL).
• Personal projects or open-source contributions demonstrating delivery capability.
• Exposure to enterprise or financial systems.

Culture & Benefits

• Defined mentorship programme and structured development path towards independent contribution.
• Dedicated time for research, learning, and staying current with AI advancements.
• Peer learning environment within a global organization.
• Strong focus on work-life balance.