About ZenteiQ ZenteiQ is building AI-powered products and software infrastructure for intelligent applications and scientific workflows. About the Role We are looking for an AI/ML Engineer to build and scale the AI capabilities powering our products. The role will focus on LLM applications, AI agents, RAG, memory, tool calling, evaluation and supporting backend services required to run these systems reliably in production. What You'll Do - Build production applications using LLMs and AI agents. - Design multi-step workflows with tool/function calling. - Build and improve RAG, retrieval and context management pipelines. - Implement conversation state and memory for AI applications. - Build structured and streaming LLM workflows. - Develop backend APIs and services supporting AI features. - Evaluate, debug and improve AI system quality and reliability. - Work with product, backend and infrastructure teams to ship AI capabilities to production. What We're Looking For - 2-6 years of AI/ML engineering experience. - Strong programming skills in Python; experience with other programming languages is a plus. - Hands-on experience building applications using LLMs. - Experience with AI agents or multi-step LLM workflows. - Good understanding of RAG, embeddings, vector search and retrieval. - Experience with tool/function calling and structured outputs. - Experience building backend APIs using FastAPI or similar frameworks. - Good understanding of asynchronous programming and databases. - Strong debugging and problem-solving skills. - Ability to take AI features from prototype to production. Good to Have / Bonus Points - LangGraph, LangChain or similar frameworks. - Vector databases and reranking. - LLM evaluation and observability. - Knowledge graphs or graph-based retrieval. - Redis or messaging/queue systems. - Docker, Kubernetes and cloud platforms. What We'll Evaluate - Python and software engineering fundamentals. - LLM and agentic workflow design. - RAG and retrieval fundamentals. - Tool calling, memory and state management. - Backend API and async programming fundamentals. - Debugging, reliability and production engineering. Why ZenteiQ - Build AI systems used in real products. - Work on LLMs, agents, retrieval and intelligent workflows. - Solve practical production problems around reliability, context and scalability. - Own AI features from development to production.