AI Engineer

Quick Facts

• Location: Kraków, Poland

Description

You will design, develop, and productionize AI and machine learning solutions to address real business challenges, including Generative AI, Large Language Models (LLMs), and intelligent automation. The role spans building AI applications and services, creating reusable AI/ML libraries, and maintaining ML/AI pipelines from experimentation to deployment, monitoring, and continuous improvement. You’ll apply modern MLOps and DevOps practices to deliver scalable, secure, and maintainable production systems.

Responsibilities

• Design, develop, and productionize AI/ML solutions for business use cases
• Implement modern approaches across ML, Generative AI, LLMs, and intelligent automation
• Build AI applications and services using Python, APIs, microservices, and cloud-native technologies
• Create reusable AI/ML libraries, frameworks, and common components
• Design and maintain ML/AI pipelines across the full lifecycle (training, deployment, monitoring)
• Build scalable, resilient, secure, and maintainable systems for production-grade AI workloads
• Apply MLOps/DevOps and software engineering practices to AI solutions
• Work with Docker, Kubernetes, cloud platforms, CI/CD, model registries, monitoring, and automation tooling
• Collaborate with engineers, data scientists, architects, and business stakeholders to turn prototypes into reliable solutions
• Help define engineering standards, architectural principles, and reusable patterns for AI development
• Evaluate emerging AI technologies and where they can create client value

Requirements

• 4+ years of professional experience in software engineering, data science, machine learning, MLOps, AI engineering, or related work
• Degree in Computer Science, Mathematics, Physics, Engineering, or equivalent practical experience
• Strong problem-solving skills and engineering mindset
• Understanding of good software engineering and application design practices
• Ability to work effectively in an Agile, collaborative environment
• Curiosity and strong desire to keep learning as AI technologies evolve
• Ability to communicate technical ideas clearly and collaborate with technical and non-technical stakeholders
• Experience in banking, financial services, or another regulated industry is welcome

Benefits

• Opportunity to experiment, build, scale, and influence how AI is applied in practice
• Work with talented teams across engineering, data, architecture, and financial services
• Collaborative, fast-moving, flexible, and entrepreneurial culture