AI Engineer (Agentic AI)

Quick Facts

• B2B contract
• Hybrid work model
• Office: ul. Chmielna 89

Description

Design, develop, and maintain agentic AI solutions used in the bank’s business processes. Build and maintain LLM-based systems including RAG (Retrieval Augmented Generation) and multi-agent architectures (e.g., Agno/LangGraph or equivalent). Integrate AI agents into enterprise systems via APIs, develop supporting ML components, and ensure production readiness through evaluation, monitoring, observability, and safety mechanisms.

Responsibilities

• Design, implement, and maintain agentic AI solutions for business processes
• Build and evolve LLM-based systems
• Design and implement RAG solutions (Retrieval Augmented Generation)
• Create multi-agent architectures using frameworks such as Agno or LangGraph (or equivalent)
• Integrate AI agents with enterprise business systems via APIs and integration services
• Develop AI components in Python
• Develop and maintain ML models supporting agentic AI solutions
• Create evaluation, monitoring, and observability mechanisms
• Optimize answer quality, reduce hallucinations, and implement AI safety and control mechanisms
• Collaborate with business teams, architects, IT teams, and security teams during AI deployments
• Design and deploy production-ready agentic AI solutions aligned with business requirements
• Build and maintain an agentic AI platform based on the Agno framework
• Deliver RAG solutions enabling secure and effective access to organizational knowledge
• Ensure high quality, stability, and observability of AI deployments
• Improve AI efficiency, cost, and quality; integrate ML components with agentic AI and LLM solutions

Requirements

• Minimum 5 years of commercial Python programming experience
• Practical experience designing and deploying LLM-based solutions
• Practical experience building RAG solutions
• Experience designing and implementing agentic AI solutions
• Knowledge of frameworks such as Agno, LangGraph, LangChain, LlamaIndex or equivalent
• Experience integrating AI solutions with business systems via APIs
• Knowledge of ML/AI libraries/frameworks: PyTorch, TensorFlow, Hugging Face
• Practical knowledge of vector databases: Qdrant, ChromaDB, Weaviate, Milvus or equivalent
• Knowledge of embeddings, reranking, and model answer quality optimization
• Experience building backend services with FastAPI
• Knowledge of AI observability and evaluation tools (e.g., Langfuse, LangSmith, Promptfoo, DeepEval)
• Knowledge of Docker and Kubernetes/OpenShift
• Knowledge of MLOps and LLMOps
• Ability to design AI architecture in enterprise environments
• Ability to collaborate with business and technical teams
• Minimum 2 years of experience designing and deploying LLM/RAG/agentic AI solutions
• Experience delivering production AI projects and integrating into enterprise architectures
• Optional: experience in the financial/banking sector or other regulated environments

Benefits

• B2B contract
• Hybrid collaboration; office in Warsaw (ul. Chmielna 89)
• Optional Luxmed and Kafeteria MyBenefit package on preferential terms