Freelance Mid-Level AI Engineer

We are looking for a remote Mid-Level AI Engineer with hands-on experience building and deploying Generative AI solutions.

📍 Remote within Europe.

This is an engineering role focused on developing production-ready applications using Large Language Models (LLMs), RAG, and cloud AI platforms such as AWS Bedrock or OpenAI APIs. This is not a research-focused position.

Before you apply, please ensure you meet the following minimum requirements:

• Professional experience developing applications in Python.
• Hands-on experience building or deploying LLM-based applications.
• Experience with RAG, OpenAI/AWS Bedrock APIs, or similar GenAI frameworks.
• Experience integrating AI solutions into production or business applications.
• Strong English communication skills.
  
  

Key Accountabilities

• Model Customization & RAG: Implement retrieval-augmented generation techniques to customize LLMs for practical business use.
• API & Platform Integration: Use AWS Bedrock, OpenAI or similar APIs to embed generative AI into existing systems.
• Applied Solution Development: Build AI-powered tools to enhance operational efficiency, decision-support systems, or customer workflows in industry settings.
• Data Prep & Collaboration: Work with data engineering to preprocess and manage data for model inputs, ensuring security and compliance.
• Performance Tuning & Production Deployment: Monitor and refine LLM deployments in scalable, reliable environments.
• Cross-Functional Partnership: Collaborate with software engineers, product managers, and stakeholders to deliver AI solutions that meet real needs.
• Documentation & Communication: Create clear documentation and explain technical concepts to both technical and non-technical audiences in a hands-on context.
  
  

Qualifications Minimum Qualifications

• Background: 1–3 years (or more) of applied experience in Software, Data, or ML Engineering (e.g., backend, data pipelines, model implementation).
• Technical Fluency: Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Cloud Experience: Familiarity with AWS, GCP, or Azure integration.
• Generative AI Passion: Interest in LLMs, prompt engineering, RAG, and applied AI, demonstrated through project work or prior deployments.
• Problem-Solving & Ownership: Ability to take a project from prototype to delivery, optimizing for performance and business value.
• Soft Skills: Clear communication, cross-functional collaboration, agile mindset.
• Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, PhD not required.
  
  

Pluses (Nice to Have)

• Experience with LLM fine-tuning, prompt engineering, or LangChain/Agent frameworks.
• Familiarity with MLOps tools (e.g., MLflow, Docker, CI/CD pipelines).
• Industry-specific experience (e.g. maritime, logistics, finance) is a bonus, but we prioritize applied engineering experience over domain knowledge.
  
  

We are looking forward to your application.