Junior AI Engineer

We are looking for a Junior AI Engineer to join our AI Enablement team and help accelerate the adoption of AI across Mobilexpense.

Working closely with and reporting to our AI Engineer, you will contribute to building internal AI-powered tools, services, and automations that solve concrete business problems. You will interact with teams across the company to understand their needs, experiment with potential solutions, and turn successful prototypes into reliable tools.

This is a hands-on role for someone early in their career who already has solid software development foundations and wants to develop strong practical expertise in generative AI and LLM-based applications.

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  Build and maintain internal AI-powered applications, tools, APIs, and automations.

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  Implement AI use cases based on requirements and technical direction provided by the AI Engineer.

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  Prototype and evaluate solutions using LLMs and other AI technologies.

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  Work with techniques such as RAG, embeddings, vector search, structured outputs, tool/function calling, and AI agents.

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  Integrate AI capabilities with existing internal systems, APIs, and data sources.

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  Test and evaluate AI solutions for quality, reliability, performance, and cost.

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  Help move successful prototypes into maintainable and production-ready solutions.

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  Collaborate with colleagues across departments to understand business processes and identify opportunities where AI can provide tangible value.

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  Contribute to documentation, reusable components, standards, and best practices for AI development.

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  Follow internal security, privacy, compliance, and AI governance requirements.

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  Stay curious about the rapidly evolving AI ecosystem and experiment with relevant new technologies.

• Degree in Computer Science, Software Engineering, AI, or equivalent practical experience.

• Good programming skills, ideally in Python and/or another modern programming language.

• Understanding of APIs, web services, databases, and modern software development practices.

• Basic understanding of generative AI, LLMs, prompting, and common AI application patterns.

• Experience with AI APIs or frameworks through professional work, internships, academic projects, or personal projects.

• Ability to learn quickly and experiment independently while knowing when to ask for guidance.

• Strong problem-solving mindset and interest in translating business needs into practical technical solutions.

• Good communication skills and ability to work with both technical and non-technical colleagues.

• Fluency in English.

• Hands-on experience building applications using LLM APIs such as OpenAI, Azure OpenAI, Anthropic, or similar.

• Experience with RAG, vector databases, embeddings, AI agents, or orchestration frameworks.

• Familiarity with Azure or other cloud platforms.

• Experience with Git, CI/CD, containers, or infrastructure-as-code.

• Experience integrating SaaS platforms and business applications through APIs.

• Awareness of AI security, privacy, responsible AI, and EU AI regulatory requirements.

• The opportunity to work on real AI use cases deployed across the company rather than isolated experiments.

• Close collaboration and mentoring from an experienced AI Engineer.

• Exposure to a broad range of business functions and AI use cases.

• Room to experiment with emerging technologies and contribute ideas.

• The opportunity to progressively take ownership of increasingly complex AI solutions as your experience grows.