Senior AI Engineer

Quick Facts

Hybrid collaboration with on-site presence in Warsaw once per week. B2B rate up to 190 PLN/h.

Description

Senior AI Engineer to design, build, and maintain production Agentic AI solutions for banking business processes. You will work on LLM systems, RAG implementations, and multi-agent architectures, integrating AI components with enterprise business systems via APIs. You will also develop ML/LLMOps capabilities including evaluation, monitoring, observability, and safety to improve response quality and limit hallucinations.

Responsibilities

• Design, develop, and maintain Agentic AI solutions used in bank business processes
• Build and maintain systems based on Large Language Models (LLMs)
• Design and implement Retrieval Augmented Generation (RAG) solutions
• Build multi-agent architectures using frameworks such as Agno and LangGraph (or equivalent)
• Integrate AI agents with business systems via APIs and integration services
• 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 response quality, reduce hallucinations, and implement AI safety/control mechanisms
• Collaborate with business teams, architects, IT, and security teams during AI deployments
• Design and implement production Agentic AI solutions according to business requirements
• Build and evolve an Agentic AI platform based on Agno
• Optimize performance, costs, and quality of AI-based solutions
• Develop ML components and integrate them with Agentic AI and LLM solutions

Benefits

• Opportunity to work across diverse projects in Software, Embedded, Data, and Cloud Services
• Involvement in additional pre-seals and expert initiatives
• Access to medical care, a sports card, and a cafeteria platform according to collaboration rules

Requirements

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