Agentic Architecture Engineer

Description:

Design and build multi-agent systems using LLMs (OpenAI, Anthropic, Gemini, etc.)

Architect agentic workflows planning loops, tool use, memory layers, and agent-to-agent communication

Design and maintain microservices that power AI agent backends, scalable, containerized, and production-ready

Integrate voice bots, chatbots, and AI agents into client products via APIs

Choose the right orchestration frameworks (LangGraph, CrewAI, AutoGen, or custom-built)

Collaborate with product and dev teams to move from brief → deployed agent

Document architecture decisions clearly for both technical and non-technical stakeholders

What We're Looking For

Strong understanding of LLM fundamentals — prompting, context windows, RAG, function calling

Hands-on experience building multi-agent or agentic AI systems (not just chatbots)

Solid microservices architecture experience — service decomposition, inter-service communication (REST, gRPC, message queues), and deployment patterns

Proficiency in Python; familiarity with LangChain, LangGraph, or similar frameworks

Experience with Docker, Kubernetes, or cloud platforms (AWS / GCP / Azure) for deploying agent infrastructure

Experience with tool/API integrations, vector databases, and memory systems

Ability to translate a business problem into an agent architecture — fast

Strong communication skills: you can explain what you built and why