You’ll be working on diverse machine learning projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery - direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment.
Requirements
Key Responsibilities
- Design and develop end-to-end agentic AI solutions using modern LLM frameworks
- Build and deploy Generative AI applications using Python
- Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows
- Implement agent orchestration for multi-agent systems and complex task automation
- Apply advanced prompt engineering techniques to optimize model performance
- Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails)
- Deploy AI solutions using container-based architectures (Docker, Kubernetes)
- Ensure scalability, reliability, and security of AI systems in production
- Integrate AI agents with enterprise APIs, databases, and external systems
- Continuously evaluate model performance and implement optimization strategies
Required Skills & Qualifications:
- Strong proficiency in Python programming
- Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, etc.)
- Experience building end-to-end agentic solutions
- Practical experience in agent development and orchestration
- Expertise in prompt engineering and LLM optimization
- Experience with container-based deployments (Docker, Kubernetes)
- Experience implementing agent observability (monitoring, tracing, evaluation frameworks)
- Knowledge of REST APIs and backend integration patterns
- Experience deploying AI applications in cloud environments (AWS / Azure / GCP)
- Understanding of RAG architectures, embeddings, vector databases
Preferred Qualifications:
- Experience with multi-agent collaboration frameworks
- Experience with evaluation tools (e.g., prompt testing, hallucination detection, guardrails)
- Familiarity with MLOps practices
- Knowledge of distributed systems design
- Experience with real-time AI applications
- Background in machine learning fundamentals
- Communicative English - minimum C1 level
It is great if you have:
Experience with DevOps / MLOps tools and practices (e.g. Docker, Kubernetes, MLFlow, KubeFlow, DVC)
Familiarity with a deep learning framework (Tensorflow, PyTorch)
Experience in using additional data science related libraries (e.g. nltk, opencv, scikit-image, gensim, plotly, seaborn, xgboost, lightgbm)
Strong general software development skills and knowledge of best practices
Algorithmic and code optimization skills
Knowledge of a cloud platform and experience in running cloud-based projects (GCP, AWS, Azure)
Salary:
20 000 - 30 000 PLN + VAT (B2B)
We offer you:
Working with the newest machine learning technologies
Budget for self-development per year
Possibility to contribute to a variety of interesting projects
Internal workshops
Personal branding (articles, conference speaker, internal workshop leader)
Flexible work hours
Remote work possibility
Chillout room / free beverages / team & company events
Friendly atmosphere
MultiSport
LuxMed

