Role overview

Bachelor’s or Master’s degree in Computer Science, Data Science, or a related discipline.
Strong software engineering skills in Python (including e.g. FastAPI, FastMCP).
Hands‑on experience building LLM applications (prompting, fine‑tuning, evaluation, structured output).
Practical knowledge of RAG architectures, embedding models, and vector databases.
Experience with AI/LLM orchestration frameworks (e.g., LangChain, LangGraph, Autogen, CrewAI).
Familiarity with cloud‑native development (Azure preferred; AWS/GCP an advantage).
Understanding of data engineering practices and ability to work with large datasets.
Experience with version control, Docker, CI/CD pipelines, and testing strategies.
Knowledge of responsible AI principles and mitigation methods is a plus.
Strong Analytical skills, innovative and a problem-solving mindset
Demonstrating ownership and technical depth.
Very good command of English (spoken and written).
Effective communication skills for cross-functional collaboration.
Remote vs Onsite: Hybrid - 2 days in the Prague office, 3 days remote, attendance to regular planning sessions/workshops required

Hackerrank: Yes

Working Overlap: Yes, minimum 2–6pm CET

What you'll work on

Design and implement end‑to‑end AI pipelines, covering data ingestion, transformation, modeling, and production deployment.

Build and refine LLM‑based applications (e.g., retrieval workflows, agentic systems, autonomous tools).

Develop reusable AI components, APIs, and automation solutions for internal and client-facing use cases.
Create robust prompt strategies, evaluation frameworks, and quality‑control methods.
Integrate embedding models, vector databases, and memory mechanisms into scalable architectures.
Collaborate with cross‑functional project teams to translate business needs into engineering deliverables.
Apply engineering best practices (testing, CI/CD, observability, performance monitoring).
Stay up to date with emerging AI frameworks, model capabilities, and cloud services.
Support responsible AI practices, including fairness, interpretability, and risk mitigation.
Consistently contribute beyond the AI remit, particularly in MLOps, ensuring seamless deployment and operations of AI solutions.
Conduct original research even in areas with limited references, driving innovation within the team.

Experience working as part of a global/multinational team
Hands-on experience with one or more cloud services (Azure, AWS, GCP)
Being up to date with the current trends and advancements in the data science field
Any experience in deep learning, computer vision and/or geo analytics is a plus
Previous experience with development using agile methodologies like Scrum or Kanban
Interest in behavioral economics and/or data science
Github profile
Ideally, we are looking for candidates with proficiency in Czech

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