At Infinidat, a Lenovo company, 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.
What you'll do
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
Requirements
System-level, end-to-end architecture view of the technical requirements and trade-offs
Ability to lead and interact with cross-functional teams in Product, R&D, OPS, SV&V
Deep hands-on experience with LLMs, agents, MCPs and the architecture of deploying a production-worthy AI system
Linux systems engineering expertise
Familiarity with enterprise storage and server hardware
Proficiency in Python and experience building data pipelines, internal tooling, and service integrations
Working knowledge of data science and analytics tooling (ETL, data warehouses, BI platforms)
A precise, measurement-first working style with the ability to analyze, and clearly present, complex architectures and concepts
An autodidact with strong communication skills
About Infinidat
Infinidat’s enterprise storage portfolio provides global Fortune 500 enterprises and service providers with best-in-class solutions for primary storage, next-generation data protection, disaster recovery, business continuity, and cyber resilience. Infinidat’s acclaimed InfuzeOS is the one of the most flexible and complete enterprise software-defined storage architectures in the industry. We recently announced powerful enhancements, an extensive expansion, and the dynamic evolution of our award-winning G4 enterprise cyber and AI storage solutions! Not only did Infinidat win over 40 awards in 2025, but was named a Gartner® Peer Insights™ Voice of the Customer Award for Primary Storage for the 7th time!