Location: Kraków

Type of contract: B2B

Salary range:  136–173 PLN net/h 

What will you do? 

You will join a team of engineers developing cutting‑edge AI and Machine Learning solutions within the Credit & Lending domain in an international banking environment. The project focuses on leveraging state‑of‑the‑art AI technologies to build scalable systems that support business processes, data‑driven decision‑making, and operational efficiency. You will work across the full lifecycle of AI/ML development—from discovery and prototyping, through model and system design, to production deployment and maintenance—using LLMs, RAG, modern data platforms, containerized environments, and cloud‑native solutions in Azure or GCP.

Your tasks

• LLM engineering and RAG development
• Designing, testing, and optimizing prompts for LLM‑based applications
• Developing and integrating RAG systems and vector search solutions
• Implementing responsible AI/ML solutions with fairness, transparency, and accountability
• Designing and building scalable architectures leveraging LLMs and ML
• Deploying AI systems using Azure or GCP with containerization and Kubernetes
• Building applications following engineering best practices and clean code principles
• Conducting data exploration, preparation, and modeling
• Collaborating with domain experts on data pipelines and domain‑specific datasets
• Applying deep learning and NLP techniques to business problems
• Working closely with engineering, product, and business stakeholders
• Presenting technical solutions, constraints, risks, and recommendations
• Participating in the full AI product lifecycle from idea to production

Your skills

• Python (3+ years); Java is a plus
• Experience with LangChain, FastAPI, Data containers, Spring
• Knowledge of microservices architecture, observability, monitoring, API design, concurrency models
• Hands‑on experience with Azure or GCP, containers, Kubernetes, CI/CD (Jenkins, Azure DevOps, GCP Cloud Build)
• Practical experience with TDD/BDD
• Strong understanding of LLM architectures and domain‑specific data modeling
• Experience with RAG, prompt engineering, agentic architectures, deep learning, NLP, ML lifecycle
• Ability to design, develop, and scale AI‑driven systems
• Strong software engineering fundamentals and problem‑solving skills
• Ability to experiment quickly and iterate toward production‑quality solutions
• Strong communication and presentation skills in English
• Ability to explain technical solutions and business implications clearly
• Comfort working with cross‑functional and multicultural teams