Software Engineer (AI/ML)

O projekcie:
At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe. 

 

Ready to engineer the future of AI in finance? Join our team to build intelligent solutions that revolutionize Credit & Lending.
 

Sounds like your kind of challenge? 

What you get in return

- Flexible cooperation model – choose the form that suits you best
(B2B, employment contract, etc.)
- Hybrid work setup – 8 days per month from Cracow office
- Collaborative team culture – work alongside experienced professionals eager to share knowledge 
- Continuous development – access to training platforms and growth opportunities 
- Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more 
- High quality equipment – laptop and essential software provided

Wymagania:
- Languages: Python (3+ years), Java (regular).
- Frameworks: FastAPI, LangChain, Spring, Data containers.
- Databases: PostgreSQL, vector databases, Redis.
- Architecture & Tools: Microservices, Kubernetes, Containers, CI/CD (Jenkins, Azure DevOps, GCP Cloud Build).
- Methodologies: TDD, BDD.
- Strong knowledge of LLMs, RAG pipelines, Prompt Engineering, and Agentic Architecture.
- Familiarity with ML, NLP, and deep learning methods.
- Excellent communication skills in English with the ability to present technical concepts to business stakeholders.

Nice to Have:

- Hands-on experience developing domain-specific LLM solutions.
- Understanding of observability, concurrency models, and API design.

 

Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.

Codzienne zadania:
- Design, test, and refine prompts for Large Language Models (LLMs) to achieve high-quality, reliable outputs.
- Build and implement Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases for insight extraction.
- Engage in the entire development lifecycle: discovery, prototyping, design, implementation, and deployment.
- Apply AI best practices ensuring fairness, transparency, and accountability.
- Collaborate across engineering, product, and business teams on solution design and architecture.
- Write and maintain clean, scalable, and testable code.
- Use Azure/GCP environments for AI model deployment and optimization.
- Maintain solutions in production and co-create architectural frameworks.