Applied AI / LLM Engineer (Python)

We’re looking for an AI Engineer to own the AI layer of our products - from research and experimentation to production deployment. You’ll have end-to-end ownership of AI initiatives, work on real-world GenAI challenges, and help shape the future of AI-powered products. Python LLM

What will need to do:

• Design and build LLM pipelines, AI agents, and RAG-based systems: function/tool calling, structured output (JSON schema)
• Develop production-grade Python services (Django, Celery, Redis)
• Validate product hypotheses using real-world data and analytics
• Measure and optimize LLM quality, performance, and cost
• Collaborate closely with product managers and engineers to turn ideas into scalable solutions, At Mad Devs, you’ll join a passionate team dedicated to solving complex challenges and delivering innovative solutions. Our projects span Europe, the USA and South East Asia, giving you the opportunity to make a global impact. We value flexibility, remote working and professional development, ensuring you thrive in an inspiring environment. Join us in revolutionizing the legal industry with AI!

Employees benefits

Flexible working hours Remote-first culture Long-term projects Salary in dollars Professional communities Onsite business trips Training budget Paid conferences Hi, I’m Ekaterina. Applying for jobs should be easy. I am here to simplify the hiring process and set you up for success. Feel free to send me a message via e-mail cv@maddevs.io

Do you have experience in gRPC?, Do you have a Master’s degree?, * Strong experience building production LLM applications

• Hands-on expertise with RAG, embeddings, vector search, prompt engineering, and LLM evaluation
• Experience with LangGraph, LangChain, or similar frameworks
• Solid Python backend background (Django, PostgreSQL, async programming)
• Strong SQL/Pandas skills and a data-driven mindset
• Language Proficiency: English at B2-C1 level, Russian at C1 level
• Location: any, except Russia and Belarus

It will be a plus:

• Experience with vector databases (Qdrant, pgvector, etc.)
• Fine-tuning, text classification, or embedding models
• Kubernetes, gRPC, or Go experience

Pulled from the full job description

• Paid training
• Flexible schedule