AI Engineer – Agentic Systems & LLM Architecture
Who We Are
AI GRID develops sovereign artificial intelligence infrastructure, high-performance GPU computing platforms, and localized cloud solutions focused on data privacy and sovereignty.
The company is expanding its engineering team to build autonomous agentic systems that can operate within scalable local and enterprise infrastructure.
About the Role
AI GRID is looking for an AI Engineer specializing in Agentic Systems and LLM Architecture.
The role focuses on designing, developing, and deploying autonomous AI agents capable of planning, reasoning, using tools, and collaborating within multi-agent systems.
You will also work on optimizing large language models for local deployment and integrating agentic workflows into production-grade platforms.
Key Responsibilities
- Design and deploy multi-agent architectures and autonomous decision-making workflows.
- Build reasoning systems using approaches such as ReAct and Tree-of-Thought.
- Develop APIs and middleware connecting AI agents with databases, enterprise tools, industrial systems, and external APIs.
- Fine-tune, quantize, and optimize large language models for low-latency local inference.
- Deploy open-source and proprietary LLMs on high-performance GPU infrastructure.
- Integrate agentic systems into production platforms with frontend, backend, infrastructure, and DevOps teams.
- Design reliable state management, memory, tool-use, and error-correction mechanisms.
- Ensure AI workflows follow strict privacy, security, and localized data-handling requirements.
Required Qualifications
- Professional experience in artificial intelligence or machine learning engineering.
- Strong experience with NLP, large language models, and autonomous AI systems.
- Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, or custom multi-agent orchestration systems.
- Advanced Python programming skills.
- Experience with PyTorch and Hugging Face Transformers.
- Experience with vector databases such as Chroma, Qdrant, or Milvus.
- Experience developing advanced retrieval-augmented generation pipelines.
- Familiarity with GPU-based model deployment and inference optimization.
- Experience with tools such as vLLM, TensorRT-LLM, or Ollama.
- Strong understanding of state management, memory retention, and error handling in complex AI workflows.
Preferred Skills
- Knowledge of industrial infrastructure, automated workflows, or control systems.
- Experience working with telecommunications or secure cloud environments.
- Contributions to open-source AI projects.
- Published research or practical work in agentic AI.
What We Offer
- The opportunity to build sovereign AI infrastructure from the ground up.
- Work on advanced autonomous and multi-agent AI systems.
- Access to high-performance GPU infrastructure, including NVIDIA RTX 5090 and RTX 6000 Pro clusters.
- Collaboration with engineering, infrastructure, backend, frontend, and DevOps teams.
- An agile and execution-focused working environment.
- The opportunity to contribute to locally deployed AI platforms focused on privacy and data sovereignty.
How to Apply
Send the following application materials:
- CV
- GitHub profile
- A brief summary of a complex AI project or agentic system you have built
Applications can be sent to: