Production AI Engineer: GenAI, Cloud & MLOps

Sii Poland; Lublin; On-site; PLN 180,000 - 240,000; Full time

Job summary

Sii Poland is seeking engineers to build AI systems that run in production, not just notebooks. You will implement end-to-end pipelines, from data ingestion to response generation, on Azure, AWS, or GCP, writing clean Python and ensuring reliability and observability.

You will collaborate with AI Architects and data engineers, tackling data quality, latency, and deployment challenges while exploring LangChain, LangGraph, and Semantic Kernel in a production context.

Qualifications

• 4+ years in software or ML engineering with production AI/ML experience
• Strong Python skills for production services
• Experience with LangChain, LangGraph, Semantic Kernel
• Hands-on with one major cloud platform (Azure/AWS/GCP)
• Experience with vector databases, embeddings, retrieval systems
• Familiar with MLOps: versioning, experiment tracking, CI/CD for ML, monitoring
• Ability to work autonomously with architects and data engineers
• Fluent English and Polish; residing in Poland

Responsibilities

• Build knowledge-grounded AI systems end-to-end: ingestion, embedding, retrieval, and response generation
• Develop agentic applications with tool integrations, planning loops, memory management, guardrails
• Implement ML pipelines for production use: prediction, classification, recommendation, and optimization
• Deploy and optimize model serving infrastructure across cloud environments
• Write clean, production-grade Python
• Build evaluation and monitoring pipelines with automated quality checks and latency tracking
• Collaborate with AI Architects and data engineers

Skills

Python

English fluency

Polish language

Autonomy

Tools

LangChain

LangGraph

Semantic Kernel

Cloud platforms

Job description

Sii Poland is seeking engineers to build AI systems that run in production, not just notebooks. You will implement end-to-end pipelines, from data ingestion to response generation, on Azure, AWS, or GCP, writing clean Python and ensuring reliability and observability.

You will collaborate with AI Architects and data engineers, tackling data quality, latency, and deployment challenges while exploring LangChain, LangGraph, and Semantic Kernel in a production context.