GenAI Engineer (Python, RAG, LLM)
Mid-level AI engineer role focused on designing and deploying GenAI solutions (RAG, LLMs) for financial clients, requiring Python expertise, cloud integration, and Agile collaboration in a B2B contract model.
Skills required
About this role
We offer a flexible collaboration model based on a B2B contract.
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.
Engagement Overview
As a GenAI Developer, you will provide services related to the design, development, and deployment of scalable AI-powered applications using Large Language Models.
Collaborating with cross-functional Agile teams, you will deliver production-ready solutions integrated into enterprise environments, helping clients unlock value from Generative AI.
This engagement is well suited to professionals passionate about GenAI who enjoy combining strong backend and cloud expertise with modern AI capabilities.
What You’ll Do
- 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
What We’re Looking For
- 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
Nice to Have
- 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
ONLINE RECRUITMENT PROCESS STEPS
1. Screening call with Recruiter
2. Technical Interview
3. Client Interview
4. Feedback / Offer
