Senior AI Agent & LLM Developer

We’re looking for a hands-on AI Developer / AI Agent Engineer to help us develop intelligent AI-powered solutions using modern LLM technologies. The project may involve building AI agents that can understand natural-language requests, access business knowledge, make decisions, interact with external tools, and automate multi-step processes. We’re particularly interested in someone who understands the difference between a simple chatbot and a reliable agentic AI system that can actually perform tasks. Key Responsibilities Depending on the specific use case, you may work on: Building AI agents capable of handling multi-step tasks Integrating OpenAI, Claude, Gemini, or other LLM APIs Developing RAG-based systems using private/company knowledge Designing multi-agent workflows with different specialized roles Implementing tool/function calling and external API integrations Connecting AI systems with databases, CRMs, SaaS platforms, and business applications Creating automated workflows triggered by AI decisions Developing AI assistants and business copilots Managing conversation history, context, and agent memory Improving prompt quality and AI response reliability Adding error handling, fallbacks, validation, and safeguards Optimizing AI applications for accuracy, speed, and cost Working with voice-based AI agents when required Example Use Case Technical Skills Strong experience with several of the following is expected: Python and/or Node.js LLM APIs RAG architecture Vector databases PostgreSQL REST APIs and third-party integrations Function/tool calling Prompt engineering AI workflow automation Agent memory and context management Backend/API development Deployment of AI applications AI Frameworks Experience with any of these is a plus: LangChain LangGraph CrewAI AutoGen LlamaIndex Similar agent/LLM frameworks Voice AI Experience with voice-based AI is a strong advantage. This could include: AI voice assistants Speech-to-text / text-to-speech systems Conversational voice agents Voice-based customer support Phone-call automation Real-time conversational AI What We Expect We’re not looking for someone who only knows how to connect an LLM API to a basic chatbot. You should understand how to turn an AI concept into a working, reliable system. You should be comfortable thinking about: How the agent decides what to do When and how it should use tools How information is retrieved How context and memory are maintained What happens when an API fails How incorrect AI responses are handled How the system can be monitored and improved How multiple agents can collaborate when needed