Senior AI Engineer/GenAI Engineer

Antal is a leading recruitment and HR advisory company, present in Poland since 1996 and later expanded to the Czech Republic and Hungary. Across the CEE region, it employs around 150 professionals delivering a full range of services from specialist and executive recruitment, employee outsourcing and HR consulting, to employer branding and market research. Its division-based structure combines deep industry expertise with functional specialisation, providing tailored solutions for companies in every sector. Antal acts as a trusted partner for both employers and candidates, guiding them through every stage of the talent journey.

• Minimum 3 years of commercial experience with Python and practical knowledge of Java.
• Experience with frameworks FastAPI, LangChain, and Spring.
• Practical knowledge of relational databases (PostgreSQL), vector databases, and key-value stores (Redis).
• Experience designing and building microservice architectures, APIs, and distributed systems.
• Experience working with cloud platforms Azure and/or Google Cloud Platform.
• Practical knowledge of containerization and orchestration with Kubernetes and CI/CD processes using Jenkins, Azure DevOps, or GCP Cloud Build.
• Knowledge of LLM architectures and experience building domain data-driven solutions.
• Practical experience in Prompt Engineering, Retrieval-Augmented Generation (RAG), and Agentic AI.
• Knowledge in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
• Experience experimenting with, deploying, and developing solutions based on Large Language Models.
• Very good command of the English language.

• Design, test, and optimize prompts for Large Language Models (LLM) to ensure high quality and reliable generated responses.
• Design and develop solutions based on Retrieval-Augmented Generation (RAG) and vector databases supporting financial data analysis.
• Participate in the entire product lifecycle from business problem identification through prototyping, design, implementation, to production deployment.
• Create, develop, and maintain high-quality, testable, and reusable code.
• Use cloud platforms Azure and/or GCP for building, deploying, and scaling AI-based solutions.
• Design and develop microservices, APIs, and integrations supporting AI solutions.
• Monitor, maintain, and optimize applications operating in production environments.
• Support technological decision-making processes and promote best practices in AI and ML solution creation.