Senior AI Engineer (LLM)

Remote job Remote February 25, 2026

Location: Poland

Contract: B2B

Salary: 25.000 - 33.000 PLN net B2B

How this role works:

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.

What you’ll work on:

  • 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

Biggest challenges in this role:

  • Greenfield project built from scratch

  • High-scale, user-facing systems with strict performance and reliability requirements

  • Designing systems meant for long-term ownership, not short-term delivery

  • Balancing model quality, latency, and cost in production LLM systems

What you’ll learn:

  • 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

What you’ll get to try and experiment with:

  • 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

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