Lead Fullstack AI/ML Engineer at GFT Poland – Kraków | Jobyssey

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

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

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