AI Data Engineer (with LLM focus)

You are a technically strong and self-driven professional with expertise in both Data Engineering and Data Science. In this role, you will effectively act as the client’s Data Scientist and Data Engineer, taking ownership of technical execution, so leadership can focus on business development and expanding client engagements. You will be involved in multiple client projects in different industries, working in a hands-on and fast-paced environment. To accelerate delivery, you’ll be encouraged to leverage VIBE coding tools such as Cursor, Codex, and similar AI-assisted technologies. Flexibility is key — you’ll sometimes extend existing pipelines, other times build new ones from scratch, always ensuring that your work is production-ready and maintainable.About the project:The customer’s company implements several client projects across various industries, working in a practical and dynamic environment. One of our client`s projects has several initiatives that are already in progress with a functioning infrastructure, while some new pipelines, microservices, and integrations need to be built from the ground up. The role involves a balanced mix of maintaining and extending existing systems, as well as greenfield development.Your area of responsibility:Design, build, and maintain data pipelines and integrations for AI-driven applications;Develop and fine-tune LLMs using frameworks such as Hugging Face and PyTorch;Implement embeddings and semantic search systems (FAISS, sentence-transformers, pgvector);Engineer prompts and build LLM-powered workflows and applications;Wrap ML models into scalable microservices using FastAPI or Flask;Deploy solutions on cloud platforms (Azure, GCP, or similar) using serverless compute;Collaborate closely with stakeholders to ensure production readiness and system scalability;Independently manage technical execution across multiple client projects.Skills and requirements:Strong proficiency in Python;Hands-on experience with Hugging Face Transformers, PyTorch, and LLM fine-tuning (LoRA/PEFT/RLHF);Experience with embeddings, semantic search, and tools such as FAISS, sentence-transformers, pgvector;Practical understanding of prompt engineering and LLM application development;Familiarity with SQL databases and data modeling;Experience with Docker and microservice architecture;Exposure to serverless compute (Azure Functions, Cloud Run, etc.);Understanding of Azure cloud stack (preferred);Knowledge of LangChain / LangGraph, scikit-learn, spaCy, pandas/numpy, FastAPI/Flask;English — Upper-Intermediate or higher.Will be a plus:Familiarity with TensorFlow / Keras (legacy compatibility);MLflow or other experiment tracking tools;Background in predictive modeling for energy trading or financial/market data;Broader data warehousing concepts (Delta Lake, etc.);Generative AI use cases beyond embeddings (summarization, narrative generation).We offer:Working in a team of talented and passionate engineers;Opportunity to work with the most trending technologies;Long-term enjoyable cooperation;Personal legal support;English classes;Payable vacation and sick days;Competitive salary depending on your own talents;Regular performance & career development reviews;Team building events.