Description
Summary We’re looking for a Senior Agentic AI / Multi-Agent Engineer to design and build production-ready AI systems that can automate real business workflows. This is not a basic chatbot or prompt-engineering role. We need someone who understands how to architect reliable AI agents, multi-agent workflows, RAG systems, tool calling, APIs, databases, cloud infrastructure, and enterprise-grade deployments. What You’ll Work On Design and develop Agentic AI systems and AI Employees Build multi-agent architectures for complex business workflows Develop AI copilots, enterprise assistants, and intelligent automation Build production-grade RAG / Knowledge systems Integrate LLMs including OpenAI, Claude, and Gemini Implement tool/function calling and API integrations Design agent memory, context management, routing, evaluation, and guardrails Build AI workflows using frameworks such as LangGraph, CrewAI, AutoGen, LangChain, or OpenAI Agents SDK Integrate databases, vector databases, enterprise data sources, and business applications Deploy scalable AI solutions on AWS, Azure, or GCP Containerize and deploy systems using Docker/Kubernetes Implement monitoring, logging, testing, security, and CI/CD Ideal Candidate You should have strong hands-on experience with: Agentic AI / Autonomous Agents Multi-Agent Systems LLM Engineering RAG and enterprise knowledge systems LangGraph / CrewAI / AutoGen / LangChain / OpenAI Agents SDK OpenAI / Claude / Gemini APIs MCP and tool/function calling Python REST APIs and microservices PostgreSQL / Snowflake / BigQuery / Databricks Vector databases AWS / Azure / GCP Docker and CI/CD What We’re Looking For We want an engineer who can take a business requirement like: “We want an AI employee that can understand incoming requests, retrieve company knowledge, make decisions, use business tools, delegate tasks to specialized agents, and complete the workflow with minimal human intervention.” …and turn that into a real, secure, scalable production system. You should be comfortable owning the architecture as well as the implementation. Nice to Have Enterprise AI architecture experience Experience building AI customer-support systems AI-powered business process automation Experience with MCP AI evaluation and observability Kubernetes Databricks / Snowflake Experience working with enterprise clients Experience taking AI prototypes into production Engagement Experience: Senior / Expert Hours: 30+ hours/week Duration: Long-term Possibility: Contract-to-hire Rate: Open to discussion based on experience To Apply Please include: A brief summary of your Agentic AI experience 2–3 production AI systems you have personally built Which agent frameworks you have hands-on experience with Your experience with RAG, MCP, tool calling, and multi-agent orchestration Your preferred cloud platform GitHub or portfolio links, if available Please do not send a generic AI-generated proposal. We’re looking for someone who can explain their architecture decisions and demonstrate real hands-on engineering experience.