AI Systems Engineer (Production AI Infrastructure)

About the role

GRQ Holdings is expanding its AI division and seeks an AI Systems Engineer to design, build, and operate production‑grade AI infrastructure. The role demands deep systems expertise and the ability to work independently across multiple technical environments.

Key responsibilities

• Design and deploy internal AI systems used across operational environments.
• Architect multi‑agent workflows and orchestration pipelines.
• Build scalable infrastructure supporting AI‑assisted execution.
• Develop and maintain Retrieval‑Augmented Generation (RAG) pipelines and vector database systems.
• Integrate APIs, LLM providers, and internal operational systems.
• Implement deterministic backend logic and automation layers using Python.
• Deploy and maintain self‑hosted services and infrastructure as needed.
• Translate operational requirements into production‑ready technical systems.

Required profile

• Strong understanding of systems architecture and AI infrastructure.
• Ability to operate independently across diverse technical stacks.
• Experience selecting appropriate architecture, tools, and deployment strategies for operational needs.
• Familiarity with agent‑first development environments and AI‑assisted engineering workflows.

Required skills

• Claude Code (CLI agents, subagents, hooks, MCP architecture, planning systems)
• OpenClaw or equivalent open‑source coding agents
• Google Antigravity or similar agent‑first development environments
• n8n (self‑hosted deployments, advanced orchestration, webhook systems, custom integrations)
• MCP server development and architecture
• Cursor / Windsurf / Codex CLI workflows
• Python backend engineering
• Vector databases and Retrieval‑Augmented Generation (RAG) systems
• LangChain / LangGraph ecosystems
• API orchestration and infrastructure integration
• Dockerized deployments and infrastructure management