AI Engineer (Agentic AI)

Quick Facts

• Role: AI Engineer (Agentic AI)

Description

You will design, develop, and maintain production solutions based on Agentic AI, Large Language Models, and Retrieval Augmented Generation (RAG). You will help evolve an Agentic AI platform, build multi-agent systems, and integrate AI solutions with business systems. You will also focus on improving response quality, limiting hallucinations, and adding evaluation and observability.

Responsibilities

• Design, develop, and maintain Agentic AI solutions used in business processes

• Build, develop, and maintain LLM-based systems

• Design and implement RAG solutions

• Build multi-agent architectures using frameworks such as Agno, LangGraph, or equivalents

• Develop an Agentic AI platform based on Agno

• Integrate AI agents with business systems via APIs and integration services

• Build and develop AI components in Python

• Develop and maintain machine learning models supporting Agentic AI solutions

• Create evaluation, monitoring, and observability mechanisms for AI solutions

• Optimize answer quality, reduce hallucinations, and develop AI safety and control mechanisms

• Optimize efficiency, cost, and quality of AI solutions

• Collaborate with business, architecture, IT, and security teams

Requirements

• Minimum 5 years of commercial Python programming experience

• Minimum 2 years of commercial experience building and deploying production solutions based on LLM, RAG and/or Agentic AI

• Practical experience designing and implementing AI agents and multi-agent architectures

• Knowledge of AI frameworks such as Agno, LangGraph, LangChain, LlamaIndex, or equivalents

• Experience integrating AI solutions with business systems via APIs and building backend services in FastAPI

• Knowledge of ML/AI libraries and frameworks, especially PyTorch, TensorFlow, and Hugging Face

• Practical knowledge of vector databases (Qdrant, ChromaDB, Weaviate, Milvus or equivalents)

• Knowledge of embeddings, reranking, and techniques for optimizing response quality

• Experience with evaluation, monitoring, and observability of AI systems (e.g., Langfuse, LangSmith, Promptfoo, DeepEval)

• Knowledge of Docker, Kubernetes/OpenShift, and MLOps/LLMOps topics

• Ability to design AI solution architecture in an enterprise environment and work with business and technical teams

Benefits

• Job stability with long-term projects and opportunities to grow across IT domains

• Flexible employment forms: B2B, employment contract, or assignment contract

• Benefits: Medicover (expanded with dentistry), FitProfit, English lessons

• F45 gym training in the office with professional trainers

• Internal referral program

• Possibility to fund IT certifications

• Hybrid/remote/on-site work depending on the project

• Company events and integration trips

• Charity support initiatives (e.g., Szlachetna Paczka, #PomagamyNexio)