AI system architect

we empower enterprises and service providers with cutting-edge Storage platforms that redefine performance, reliability, and cyber resilience at scale. As an AI system architect, you will design and build the AI infrastructure that powers Infinidat's internal engineering and data platforms. Working alongside our AI platform lead, you will architect the Full Stack - from air -gapped LLM inference clusters and RAG pipelines to the chatbot front door and MCP/Skills ecosystem that put these capabilities in the hands of R&D teams. This is a hands-on role for someone who thrives at the intersection of systems engineering, data infrastructure, and applied AI.
Responsibilities:
* Architect the Infinidat AI offering roadmap, in terms of HW, SW and AIOps
* Design the future products of Infinidat to maximize the AI offering in terms of performance, cost and power
* Architect and design on-premises LLM inference infrastructure, including multi-model serving on GPUs, high-core-count servers, systemd-managed services, context/throughput tuning, and network isolation for air-gapped deployments
* Design and extend Retrieval-Augmented Generation (RAG) pipelines - document parsing, chunking, embedding, governance definition, and hybrid vector Storage - for both document and source-code collections
* Build and maintain the internal AI platform architecture, including the chatbot front-door layer, model routing, an MCP/Skills marketplace, and data -sanitization boundaries between on-prem and cloud
* Develop internal Developer tooling and agentic coding workflows, integrating local model endpoints with editor and CLI-based coding assistants - Contribute to hardware evaluation and reliability modeling for server and Storage platforms, informing infrastructure decisions with quantitative analysis
* Establish operational discipline around security, reproducibility, and maintainability - favoring durable architectural solutions over per-case patches