Lead Fullstack AI/ML Engineer

GFT Poland is delivering enterprise-grade AI and machine learning solutions for global organizations.

• 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

• 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