AI Engineer (AI/ML)

Mindbox is a tech-driven company connecting top IT talents with technology projects for leading enterprises across Europe. The team consists of six engineers working on innovative AI and ML projects delivering high-impact solutions in a fast-moving and stable environment, collaborating closely with business stakeholders to solve real-world financial challenges using advanced technologies.

• 3+ years experience with Python.
• Regular experience with Java.
• Experience with FastAPI, LangChain, Data containers, and Spring frameworks.
• Knowledge of SQL (PostgreSQL), vector databases, and key-value stores (Redis).
• Understanding of microservices architecture, observability, API design, and concurrency models.
• Experience with Azure, GCP, containers, Kubernetes, and CI/CD tools (Jenkins, Azure DevOps, GCP Cloud Build).
• Practical experience in Test-Driven Development (TDD) and Behavior-Driven Development (BDD).
• Understanding of Large Language Model (LLM) architectures and their application to domain-specific data.
• Experience with Retrieval-Augmented Generation (RAG), prompt engineering, and agentic architecture.
• Knowledge of machine learning, deep learning, and natural language processing (NLP).
• Strong communication and presentation skills in English.

• Design, test, and optimize prompts for Large Language Models (LLMs) to ensure high-quality, reliable outputs for Credit & Lending use cases.
• Develop and implement sophisticated solutions using Retrieval-Augmented Generation (RAG) and vector databases to extract insights from complex financial data.
• Participate in the full lifecycle of solutions, from problem discovery and prototyping to design, implementation, and production deployment.
• Apply AI best practices to ensure fairness, transparency, and accountability in all models and applications.
• Collaborate with engineers, product managers, and business experts to align technical efforts with strategic goals.
• Write and maintain high-quality, testable, and reusable code.
• Utilize cloud platforms (Azure, GCP) for development, deployment, and scaling of AI models.
• Co-author solution designs and architecture and maintain products in production.