Senior AI Engineer (LLM)

You will start by building the system as part of our team, working in a focused, greenfield setup. After a few months of introduction to the project, you will seamlessly continue working on the same product directly with the client, becoming part of the client’s team responsible for its long-term development and scaling. There is no handover phase and no context switching - you stay with the same codebase, product, and technical challenges, while gaining long-term ownership and impact.

• Designing, implementing, and deploying end-to-end NLP and deep learning systems

• Building LLM-powered applications that interact with real users

• Developing and maintaining production Python services

• Exposing models and pipelines via REST APIs (FastAPI, Flask)

• Working on retrieval models and techniques (RAG, embeddings, ranking)

• Evaluating, monitoring, and continuously improving model and system quality

• Scaling systems to handle enormous volumes of requests
  

• How to build LLM-powered products from scratch and take them to production

• Proven approaches to running LLMs in production at scale

• How to design, evaluate, and evolve NLP systems used by real users

• Best practices for production ML and AI system architecture
  

• At least 4 years of experience in ML / AI engineering

• Proven experience owning production NLP or LLM systems

• Strong understanding of Transformer architecture and deep learning foundations behind modern LLMs (attention mechanisms, self-attention, positional encoding, encoder–decoder vs decoder-only models)

• Proven experience designing, fine-tuning, and deploying end-to-end NLP and deep learning solutions in production environments

• Hands-on experience building LLM-powered production systems (e.g. GPT, Claude, Gemini), including prompt engineering, evaluation, supervised fine-tuning (SFT), instruction tuning, and parameter-efficient fine-tuning methods (e.g. LoRA, adapters), as well as user-facing integrations

• End-to-end ownership of LLM-based systems

• Optimizing retrieval models, RAG pipelines, and inference workflows

• Experimenting with different LLMs, prompting strategies, and system designs

• Solving performance and reliability challenges under heavy traffic

• Work with an experienced team that continually shares knowledge and is not afraid of testing new solutions

• Flexible hours

• Individual work tools – Macbook Pro, Dell screen, JBL headphones? You can tailor the equipment to your needs

• Sport & wellness benefit (Kafeteria MyBenefit)

• Private medical care

• A comprehensive benefits package after transitioning to our partner, including employee benefits, training opportunities, and occasional bonuses