AI Engineer – GenAI & Cloud (f/m/x)

Nasze wymagania: At least 4 years in software or ML engineering, with hands-on experience shipping AI/ML systems to production Strong Python skills — not just scripting, but writing maintainable, tested code for production services Practical experience with AI/ML frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent Working knowledge of at least one major cloud platform (Azure, AWS, or GCP) and its AI/ML services Experience with vector databases, embedding models, and retrieval systems in real-world applications Familiarity with MLOps fundamentals: model versioning, experiment tracking, CI/CD for ML, and monitoring Ability to work autonomously while collaborating effectively with architects, data engineers, and product teams Fluent English (both written and spoken) Mile widziane: Experience fine-tuning LLMs (LoRA, QLoRA) or working with model training pipelines Background in classical ML — scikit-learn, XGBoost, time series forecasting, or recommendation systems Experience with containerized deployments (Docker, Kubernetes) and infrastructure-as-code Contributions to open-source AI/ML projects or published technical writing O projekcie: We need engineers who build AI systems that work outside of a Jupyter notebook. You’ll take architectures designed for real problems and turn them into production services — reliable, observable, and cost-efficient. Your day-to-day will involve writing Python, wiring up cloud infrastructure, and solving the unglamorous problems that make AI actually useful: data quality, latency, evaluation, and deployment. You’ll work across the generative and classical AI stack — building knowledge-grounded AI systems, integrating LLMs into applications, training and deploying traditional ML models, and keeping it all running in production on Azure, AWS, or GCP. Zakres obowiązków: Build and deploy knowledge-grounded AI systems end-to-end: data ingestion, chunking, embedding pipelines, retrieval logic, re-ranking, and response generation Develop agentic applications — tool integrations, planning loops, memory management, guardrails — using frameworks like LangGraph, LangChain, Semantic Kernel, or equivalent Implement and maintain ML pipelines for classical use cases: prediction, classification, recommendation, and optimization models Deploy and optimize model serving infrastructure: API endpoints, batching, caching, GPU utilization, and cost management across cloud environments Write clean, tested, production-grade Python — not prototype code that someone else has to rewrite Build evaluation and monitoring pipelines: automated quality checks, drift detection, latency tracking, and human-in-the-loop feedback loops Work with cloud-native AI services on at least one major platform (Azure, AWS, or GCP) to implement scalable solutions Collaborate with AI Architects on technical design and with data engineers on data availability and quality Oferujemy: AI Grant — Stop talking about AI and start building it. Our AI Grant gives you dedicated budget and resources to turn your wildest AI idea into a working project, backed by two paid weeks to focus on nothing else. AI Center of Excellence — Work alongside specialists in agentic AI, sovereign AI, generative and discriminative AI. This isn’t a siloed team — it’s the people you’ll learn from and build with daily. Your tools, your choice — Full access to AI-powered development tools including Claude, Cursor, and GitHub Copilot. Pick what works best for you. Real project variety — From generative AI for legal document compliance, through agentic systems in manufacturing environments, to enterprise-scale AI platforms, computer vision, and autonomous driving. You won’t get bored. Conference and speaking support — Want to attend conferences? We’ll back you. Want to speak at them? Even better — we’ll support you with dedicated preparation time and bonuses.