GenAI Engineer (Python,RAG,LLM)

We are looking for a Poland-based candidate. This is hybrid role 1-2 times from Kraków office per month. 

We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on innovative AI and automation initiatives for leading financial institutions.

At Capco Poland, we're not just another consultancy – we're the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we help clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management.

As a GenAI Developer , you will play a key role in designing, building, and deploying scalable AI-powered applications using Large Language Models.

Working in cross-functional agile teams, you’ll deliver production-ready solutions integrated into enterprise environments, helping clients unlock real value from Generative AI.

This role is ideal for an engineer passionate about GenAI, who enjoys combining strong backend and cloud skills with modern AI capabilities.

• Design, build, and deploy AI applications leveraging LLMs
• Develop scalable solutions using GCP services (Vertex AI, BigQuery, Cloud Run / Functions)
• Integrate LLM APIs (e.g. OpenAI, Vertex AI) into enterprise systems
• Design and implement RAG architectures
• Apply prompt engineering techniques to optimize model performance
• Build and maintain REST APIs and microservices
• Collaborate with cross-functional teams including data, backend, and business stakeholders
• Deliver high-quality solutions in agile, client-facing environments

• 3–6 years of experience in software development
• Strong hands-on experience with Python
• Experience with Google Cloud Platform (Vertex AI, BigQuery, Cloud Run / Functions)
• Practical experience working with LLM APIs (OpenAI, Vertex AI, etc.)
• Understanding of prompt engineering and RAG architectures
• Experience building REST APIs and microservices
• Strong communication skills and ability to work in a consulting environment

• Experience with LangChain or LlamaIndex
• Knowledge of embeddings and vector search
• Exposure to LLMOps / MLOps on GCP
• Understanding of AI governance and security
• Experience in banking or regulated environments

1.Screening call with Recruiter

2.Technical Interview

3.Client Interview

4.Feedback / Offer