Consulting Engineer, Infrastructure & AI Architecture

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Lenovo is seeking an experienced Architect specializing in infrastructure and software architecture to shape how AI workloads are designed, placed, and scaled across on-premises data centres, edge environments, and public cloud.

This is an architecture leadership role: you will own the reference architectures, decision frameworks, and technical standards that guide how our teams build and run AI systems, and youwill act as the trusted advisor who translates business and research objectives into implementable designs. Working across research, engineering, IT, security, and product, you will make and defend the trade-offs that determine performance, portability, compliance, and cost across the hybrid estate.

If you are passionate about making Smarter Technology For All, come help us realize our Hybrid AI vision!

Acting as the owner of the design and governance of the platform, you will be directly responsible for the design, delivery, governance and the cost-effective use of the infrastructure. You will ensure that it meets the demands of varied consumers across Lenovo AI Technology Centre and wider across the CTO Organisation.

You will work in partnership with the Project Strategy Director and the AI Technical Director, and while not directly having line management responsibility you will coordinate with the other leaders to ensure correct prioritisation of technical platform progression alongside business value.

You will be responsible for ensuring best practice in software engineering is consistently adopted and adhered to across the UK sites and influence other wider sites.

You will be connected to the wider LATC architecture team and you will drive for alignment and ensure knowledge is signposted and shared continuously through a proactive communication approach.

Responsibilities

• Own the end-to-end reference infrastructure architecture for workloads spanning the on-premise server and public cloud compute and GPU estate. Define the patterns teams use for hosting, compute, data pipelines, training and fine-tuning, model serving, and retrieval-augmented systems.
• Workload Placement and Portability: Establish the decision framework that determines where a given workload runs, weighing data gravity, sovereignty, latency, accelerator availability, and cost. Design for portability so workloads can shift between environments without re-engineering.
• Architecture Governance and Standards: Chair design reviews, maintain architecture decision records, and define the golden patterns and guardrails that delivery teams build against. Serve as the technical approval authority for…