Job description10+ years of experience in data architecture, distributed systems, or ML platform engineering.- Deep experience building on-premises or hybrid data systems (e.g., Spark, Kafka, Trino, Iceberg, Airflow).- Strong understanding of LLM architecture, embeddings, vector search, and agentic workflows.- Proven experience designing and implementing ML pipelines, inference runtimes, and data retrieval frameworks.- Proficiency with at least one programming language (e.g., Python, Go, Java) and AI / ML frameworks (e.g., LangChain, Haystack, Hugging Face Transformers).- Demonstrated expertise in designing and building scalable, production-grade RESTful APIs, enabling seamless integration across distributed systems and AI-powered applications.Preferred : - Experience working with LLM orchestration frameworks, retrieval-augmented generation (RAG), and prompt engineering strategies.- Familiarity with open-source projects like LangGraph, AutoGPT, CrewAI, and ReAct-based agent architectures.- Strong communication skills and a track record of delivering complex systems in fast-paced environments.