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LLM / Prompt Engineer
New
AI/ML

LLM / Prompt Engineer

Type of work
Full-time
Experience
Senior
Employment Type
B2B
Operating mode
Hybrid

Tech stack

    English

    B2

    Python

    master

    SQL

    master

    CI/CD

    advanced

    Azure

    advanced

    Google Cloud Platform

    advanced

    GitHub

    nice to have

Job description

Contract: B2B, long-term

Industry: Banking

Location: Hybrid (see below)


Hybrid work:

  • Kraków and nearby – 5 office days per month
  • Warsaw and nearby – 3 office days per month (office in Warsaw)
  • Outside Kraków and Warsaw – 1 day per month or 3 days per quarter (e.g. one longer visit)


About the Role

The primary goal of this role is to leverage Large Language Models (LLMs) to develop innovative AI solutions that solve real business challenges. You’ll focus on fine-tuning models, optimizing prompts, and integrating LLM-based systems like RAG into enterprise applications.


Main Responsibilities

  • Design, test, and optimize prompts for diverse use cases (e.g., document generation, summarization, information extraction).
  • Fine-tune pre-trained LLMs using domain-specific data to improve contextual accuracy.
  • Develop solutions using Retrieval-Augmented Generation (RAG) integrated with Vector Databases.
  • Guarantee compliance with ethical AI principles (fairness, transparency, accountability).
  • Collaborate with business stakeholders to ensure solutions align with goals.
  • Contribute to the development of NLP, ML, and AI components.
  • Work in Python, use SQL, GitHub, and CI/CD pipelines.
  • Deploy and manage solutions on Azure or GCP (depending on the candidate’s stronger side).
  • Present technical insights to both technical and non-technical audiences.


Tech Stack & Environment

  • LLMs + RAG + Vector DBs
  • Languages: Python, SQL
  • Tools: GitHub, CI/CD
  • Cloud: Azure and/or GCP
  • Framework: Not strictly defined yet – the selected candidate will help shape it.


Use Cases

  • Prompt engineering for document summarization, content generation, and information extraction.
  • RAG-based applications, such as chatbots, use internal company documentation.


Key Requirements (5+ years of experience):

  • Deep understanding of LLM architectures and experience with fine-tuning.
  • Strong knowledge of RAG, prompt engineering, and vector databases.
  • Solid background in NLP, ML, and AI development.
  • Experience with Python and SQL; CI/CD practices.
  • Proficiency with Azure or GCP.
  • Strong communication skills in English, including the ability to present complex topics.


Recruitment Process

  • 2-stage process: technical + soft skills.
Undisclosed Salary

B2B

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