We are looking for an experienced GenAI Engineer to build and scale backend services for AI-powered chat and agentic systems. The role combines strong backend engineering fundamentals with deep expertise in LLM integration, prompt engineering, and agentic workflow design, including data ingestion and retrieval pipelinesResponsibilities Design, build, and maintain backend services primarily in Python (with Go or Rust as a plus) Integrate and orchestrate LLMs for chat and agentic workflows Design and improve prompt engineering, prompt chaining, and tool/function calling Build data ingestion pipelines (parsing, normalization, chunking, enrichment)Implement and optimize RAG pipelines including embeddings, vector search, and reranking Work with PostgreSQL and vector databases (e.g., Qdrant) Develop scalable and reliable systems running on Kubernetes Contribute to system scalability and performance as well as bug fixing and stability Ensure observability, reliability, and clean engineering practices in production systems Requirements 5+ years of experience as a backend engineer Strong proficiency in Python (FastAPI, Django, or similar frameworks) Hands-on experience with LLM-based systems (chatbots, assistants, agents) Experience with prompt engineering and agentic workflows Solid experience with RAG architectures, including chunking and reranking Experience with vector databases Strong understanding of backend system design and scalability Experience with Kubernetes and cloud-native architectures Experience with PostgreSQL Nice to Have Experience with Go or Rust Familiarity with agent frameworks (LangChain, LlamaIndex, etc.) Experience with AI evaluation, monitoring, and observability Experience with high-load or real-time systems