higher education in the field of computer science or related education,
advanced knowledge of Python and experience in SDLC (min. 3 years),
knowledge of cloud platforms: AWS, Azure or GCP,
experience in working with SQL and NoSQL databases,
in-depth understanding of LLMs: transformers, embedding, tokenization and API integration,
proficiency in prompt engineering and LLM orchestration tools (LangChain, LangGraph, Semantic Kernel, Crew AI),
experience in using vector databases (Pinecone, PGVector, Weaviate, FAISS, Milvus) in GenAI solutions,
high software engineering skills in Python, knowledge of coding standards and good practices,
experience in code review, debugging, testing and working with version control systems,
knowledge of CI/CD and automation tools (GitHub, Azure DevOps, Docker, Kubernetes),
experience in containerizing AI solutions and implementing them in enterprise environments,
the ability to integrate logging, monitoring and alert systems,
the ability to solve problems based on systemic thinking and the so-called first principles,
the ability to design scalable, resilient and secure systems,
experience in API design, event architectures, microservices, serverless and containers,
knowledge of enterprise integration patterns (messaging, pub/sub, event sourcing),
knowledge of IAM, RBAC, secret management and network security (VPCs, firewalls).
