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