Senior GenAI Engineer (Python)

TL;DR

Senior GenAI Engineer (Python): Building production-ready AI features and agentic workflows for a cloud-based enterprise planning platform with an accent on model integration, RAG implementation, and prompt engineering. Focus on optimizing LLM inference pipelines, ensuring system scalability, and developing end-to-end AI services within a greenfield team.

Location: Must be based in Romania (remote) or Budapest, Hungary (hybrid)

Company

Zenitech is a leading international technology solutions provider specializing in digital transformation, R&D labs, and specialist development talent.

What you will do

• Develop end-to-end GenAI features including backend API services, model integration, and deployment.
• Optimize LLMs for business planning use cases using prompt engineering and RAG implementation.
• Build conversational interfaces and agentic workflows to simplify complex planning tasks.
• Implement evaluation frameworks to measure and improve AI feature quality, accuracy, and latency.
• Design and develop APIs to expose AI capabilities to the client platform and third-party integrations.
• Collaborate with data scientists to productionize ML models and forecasting algorithms.

Requirements

• 5+ years of software engineering experience with 2+ years focused on ML/AI systems.
• Strong programming skills in Python and ML frameworks like PyTorch or TensorFlow.
• Proven experience building and deploying LLM-powered applications in production.
• Solid understanding of RESTful API design, microservices, and cloud infrastructure.
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Must be based in Romania or Budapest, Hungary.

Nice to have

• Experience with GenAI frameworks like LangChain or LlamaIndex.
• Knowledge of vector databases such as Pinecone or Weaviate.
• Familiarity with model serving frameworks like vLLM or Ray.
• Background in forecasting, planning, or analytics applications.
• Experience with model observability tools like LangSmith or MLflow.

Culture & Benefits

• Hybrid or flexible working model with flexible hours.
• Private medical and health insurance.
• Continuous growth support through a People Lead system and training resources.
• Inclusive environment with a community-first mindset.
• Location-specific benefits including cafeteria packages and meal tickets.