AI Systems Engineer for Production AI Platform

We are looking for an experienced AI Systems Engineer or AI Architect to design and build a production-grade AI platform that combines AI agents, Retrieval-Augmented Generation (RAG), and intelligent workflow automation. Our goal is to move beyond prototypes and create a scalable, reliable system that can be deployed into real business environments and support operational processes, decision-making, and automation. The ideal candidate has hands-on experience building and deploying AI systems in production and understands how to connect AI models with business workflows in a practical and scalable way. The system will include AI agents capable of reasoning, planning, and executing multi-step tasks while interacting with external APIs, internal tools, and business systems. It should also include a robust RAG architecture with document ingestion, embedding pipelines, vector database integration, and hybrid search to enable accurate and context-aware knowledge retrieval. In addition to the AI layer, the platform should support workflow automation across business operations, including integrations with CRM platforms, third-party services, and event-driven processes. Experience designing modular architectures, handling failures gracefully, implementing logging and monitoring, and ensuring long-term maintainability is important. We are particularly interested in candidates who have worked with technologies such as LangGraph, LangChain, CrewAI, AutoGen, OpenAI, Claude, vector databases such as Pinecone, Weaviate, or Qdrant, and backend frameworks such as Python and FastAPI. Experience with automation platforms such as n8n, Zapier, or Make, along with cloud deployment on AWS, Azure, or GCP and containerization using Docker, is highly desirable. Experience with voice AI solutions is a plus. This may include speech-to-text, text-to-speech, real-time voice agents, call transcription, conversation reasoning, and post-call automation integrated with CRM systems. When applying, please share examples of AI agents, RAG systems, automation platforms, or other production AI solutions you have built. We are looking for someone who can architect and implement real-world AI systems that deliver measurable business value rather than simple demos or proof-of-concept applications.