Lead Fullstack AI/ML Engineer

What will you do? Join a team delivering enterprise-grade AI and machine learning solutions for global organizations. You will be responsible for the end-to-end delivery of AI products, from architecture and development through deployment and production support. Working closely with business stakeholders, you will build scalable, secure, and compliant AI applications, conversational assistants, agent-based systems, and cloud-native platforms that create measurable business value. We offer Hybrid work in our client's office (Kraków) 8 days a month Working in a highly experienced and dedicated team Benefit package tailored to your needs (medical, sport, lunch subsidy, life insurance, etc.) Online training and certifications Access to e-learning platform Social events Daily tasks: - Collaborate with business stakeholders and translate requirements into scalable AI solutions - Design, build and deliver production-grade AI and machine learning systems - Develop AI assistants, chatbots, agentic workflows and RAG-based applications - Design scalable cloud, data and AI architectures - Develop frontend and backend services, APIs and enterprise integrations - Implement MLOps and LLMOps processes including monitoring, evaluation and governance - Build and maintain AI deployment pipelines and automation frameworks - Provide post-production support and continuous optimization of live solutions - Ensure security, reliability, performance and compliance across AI platforms 7+ years of software engineering experience with 3+ years delivering production-grade AI or machine learning solutions Experience delivering end-to-end AI systems from concept through production deployment Hands-on experience building conversational AI, chatbots, assistants or agent-based solutions Expert-level Python development skills and software engineering best practices Knowledge of software design patterns, automated testing and microservices architectures Hands-on experience with Docker, Kubernetes and deployment automation Experience with cloud platforms such as Microsoft Azure, AWS or GCP Practical knowledge of enterprise LLMs including GPT, Claude, Gemini, Llama or Mistral Hands-on experience with prompt engineering, function calling, structured outputs and workflow orchestration Experience building agent-based systems, tool integrations and human-in-the-loop workflows Knowledge of LangGraph, LangChain or Google ADK Experience with traditional machine learning techniques and model evaluation Hands-on experience with PyTorch, TensorFlow or Scikit-learn Experience with MLflow, Kubeflow or cloud-native MLOps platforms Knowledge of monitoring, observability, model governance and performance optimization Nice to have Experience with LlamaIndex, Semantic Kernel, AutoGen or CrewAI Experience with large-scale enterprise AI transformation programs Knowledge of model explainability and responsible AI practices Experience with cost optimization and AI platform governance Exposure to multi-agent architectures and autonomous task execution Must have: Python, AI, Microservices architecture, Automated testing, Docker, Kubernetes, Cloud platform, LLM, LangGraph, Google ADK, Machine learning, PyTorch, TensorFlow, scikit-learn, MLOps, MLflow, Kuberflow Nice to have: LlamaIndex, Semantic Kernel, AutoGen, CrewAI