AI/LLM Operations Engineer

Quick Facts

• Role: AI/LLM Ops Engineer

Description

Own end-to-end delivery of production AI projects, including AI agents, RAG pipelines, chatbot engines, and autonomous automations that run unattended. Build and maintain LLM-powered services with a focus on quality, reliability, data sensitivity, and measurable service health (latency, costs, and output quality). Integrate solutions into broader product infrastructure via APIs and data models.

Responsibilities

• Own client AI projects end to end, from scoping through delivery
• Build and maintain AI agents and orchestration flows with Python and LangChain/LangGraph
• Design and operate chatbot engines (session handling, persistence, state across turns)
• Build and improve RAG systems (ingestion, chunking, embeddings, retrieval, grounding)
• Develop autonomous automations for scheduled/overnight unattended workflows
• Monitor LLM services in production (latency, costs, output quality over time)
• Adapt solutions for on-premise deployments using open-source/open-weight models
• Integrate AI features into product infrastructure (APIs, data models)
• Participate in code reviews and contribute technical documentation
• Maintain CI/CD pipelines using GitHub Actions or similar tools

Requirements

• Python as your primary language
• Experience building AI agents with LangChain/LangGraph
• Practical experience with RAG systems
• Experience building chatbot engines with session durability, persistence, and state
• Familiarity with autonomous systems and unattended/scheduled AI workflows
• Working knowledge of open-source/open-weight models and on-premise deployment
• Clear communication and strong ownership
• Ability to write code that others can read and extend
• Comfort with Git, Docker, and CI/CD

Benefits

• Salary PLN 20,000–28,000 depending on experience
• Fully remote or hybrid (central Warsaw office)
• Flexible working hours based on output
• Benefits: Multisport & Medicover
• High-ownership projects with real technical depth and learning
• Early-stage opportunity to shape scaling and growth