Consulting Engineer, Infrastructure & AI Architecture

Consulting Engineer, Infrastructure & AI Architecture

Full-Time 72000 - 88000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Design and optimise AI infrastructure across cloud and on-premises environments.
  • Company: Join Lenovo, a global tech leader with a commitment to innovation.
  • Benefits: Enjoy private medical insurance, work-life balance, and discounts on Lenovo products.
  • Other info: Collaborate with diverse teams and drive innovation in a supportive culture.
  • Why this job: Shape the future of AI technology and make a real impact in a dynamic environment.
  • Qualifications: 10+ years in software or infrastructure engineering, with strong architecture skills.

The predicted salary is between 72000 - 88000 £ per year.

We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere.

Description and Requirements

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 you will 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 significant AI platform designs.
  • Connectivity, Identity, and Data Architecture: Design the secure network topologies, federated identity and access models, and cross-environment data architectures that make a hybrid estate coherent, including dedicated interconnects, private endpoints, replication, and residency controls.
  • Cloud Economics and TCO Modelling: Build and defend total-cost and unit-economics models comparing owned GPU capacity against cloud consumption, accounting for egress, commitments, and burst strategies. Inform buy-versus-build and capacity investment decisions with evidence.
  • Technical Advisory and Enablement: Partner with software engineers, data scientists, ML engineers, platform engineers, product managers, and security to turn objectives into architecture and architecture into actionable roadmaps. Mentor engineers and fellow architects, and raise the design bar across the organization.
  • Security, Compliance, and Resilience by Design: Embed access controls, regulatory requirements, and resilience and disaster-recovery patterns into architecture from the outset, working alongside security, legal, and compliance functions rather than retrofitting after the fact.

Qualifications

  • Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Advanced degree preferred.
  • 10+ years of experience in software, infrastructure, or platform engineering, including at least 3 years in a dedicated architecture or solution architecture role and 3 years working on Data, Cloud, AI/ML platforms or workloads.
  • Demonstrated ownership of enterprise-scale hybrid or multi-cloud architectures spanning on-premises and public cloud environments, from design through adoption.
  • Deep expertise in at least one major cloud platform (AWS, Azure, or GCP) with working knowledge of a second, alongside practical experience with on-premises and private cloud infrastructure.
  • Strong grounding in hybrid networking: dedicated interconnects, transit and routing design, DNS, private service endpoints, and hybrid identity and federation models.
  • Experience designing data architecture across environments, including storage tiering, replication and caching strategies, and the residency and sovereignty constraints that shape them.
  • Sufficient hands-on fluency with infrastructure-as-code and automation (e.g., Terraform, Ansible, Kubernetes tooling) and working proficiency in Python to prototype, validate, and stress-test your own designs.
  • Track record of building capacity and total-cost models that withstand scrutiny from engineering, finance, and executive stakeholders.
  • Excellent written and verbal communication, with strong architecture documentation, decision records, and the presence to present and defend designs to senior leadership.
  • Ability to influence without direct authority, build consensus across engineering, security, and business stakeholders, and drive clarity in a fast-paced, ambiguous environment.

Bonus Points

  • Recognized architecture certification (AWS/Azure/Google Professional Cloud Architect, TOGAF, or equivalent).
  • Familiarity with private and hybrid cloud platforms (e.g., VMware, OpenShift, Nutanix, Azure Stack, AWS Outposts).
  • Expertise with observability and FinOps tooling across hybrid estates (e.g., Prometheus, Grafana, ELK/OpenSearch, Datadog, cloud cost management platforms).
  • Experience architecting under data sovereignty, regulated industry, or public sector constraints.
  • Contributions to open-source infrastructure or ML tooling projects, or published architecture writing and conference talks.

What Lenovo can offer you:

  • Private medical insurance, income protection, life insurance, and an attractive pension scheme.
  • Strong focus on work–life balance, learning, and development.
  • Lenovo and Motorola product discounts plus lifestyle discounts.
  • Cycle to work programme and gym discounts.
  • Mortgage advice and financial wellbeing support.
  • Employee referral bonus.

LATC We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.

Consulting Engineer, Infrastructure & AI Architecture employer: Lenovo

As a Retail Sales Trainer for Lenovo and Motorola, you will thrive in a dynamic work environment that values innovation and teamwork. Our London-based team is dedicated to fostering employee growth through comprehensive training programmes and opportunities to engage with cutting-edge technology. Join us to not only enhance your skills but also to make a meaningful impact on retail teams while representing globally recognised brands.

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Contact Details:

Lenovo Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Consulting Engineer, Infrastructure & AI Architecture

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We think you need these skills to ace Consulting Engineer, Infrastructure & AI Architecture

Infrastructure Architecture
Software Architecture
AI Workloads Design
Cloud Computing (AWS, Azure, GCP)
Hybrid Networking
Data Architecture
Infrastructure-as-Code (Terraform, Ansible, Kubernetes)

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Lenovo.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Lenovo and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Lenovo

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Lenovo uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.