Adamus S.A. · Szczecin
Architected and deployed an enterprise multi-agent system on Azure, incorporating prompt engineering to automate the quotation process.
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AI Engineer specializing in AI Agents, Prompt Engineering and Azure Solution Architecture — designing secure, scalable agentic workflows and enterprise systems that bridge AI models with robust Azure architecture and system security.
01 — who I am
I build agentic AI systems that turn language models into dependable enterprise tools. My work spans the full stack of modern AI engineering — from prompt engineering and agent orchestration with LangGraph & LangChain, to secure Azure architectures and MLOps pipelines that keep models measurable and production-ready.
Previously a software and robotics engineer, I bring a pragmatic, systems-first mindset: clean APIs, reproducible experiments, and security baked in from the start.
Designing multi-agent systems with clear boundaries, structured outputs and human-in-the-loop safety.
Deploying on Azure with architecture focused on scalability, observability and security.
PyTorch + MLflow experimentation, reproducible training and measurable evaluation.
02 — toolbox
03 — career path
Architected and deployed an enterprise multi-agent system on Azure, incorporating prompt engineering to automate the quotation process.
Designed scalable backend architecture and APIs for spatial and simulation platforms using Docker and PostgreSQL.
Programmed a collaborative robot (cobot) to synchronize movements with human motion captured via computer vision.
04 — selected work
★ Featured project
Advanced Reinforcement Learning (SAC / PPO / A2C) for autonomous Robot Sumo combat — featuring competitive self-play in continuous action spaces.
Chrome extension that enhances the Gemini web experience.
Quadcopter control system simulation based on linear controllers with extensive visualization.
High-fidelity simulation of rocket flight dynamics and control — ideal for ML/RL training and GNC research.
Multiparadigm DQN + Imitation Learning project focused on solving a 2×2 Rubik’s cube.
ML model for collision detection trained on accelerometer sensor data with PyTorch.
RAG-based application that answers questions and generates quizzes & flashcards from provided materials.
05 — background
Poznan University of Technology
Department of Automation, Robotics and Electrical Engineering
Poznan University of Technology
Department of Computer Science
Harvard University
EITCA
EITCA
EITCA
06 — contact
Open to AI engineering roles, agentic-system projects and Azure architecture challenges. Drop me a line — I usually reply within 24 hours.