At a Glance
- Tasks: Lead the design and delivery of next-gen AI platforms using Kubernetes and cloud technologies.
- Company: Join Lenovo, a leader in innovative tech solutions with a collaborative culture.
- Benefits: Enjoy career growth, flexible hybrid work, and performance-based rewards.
- Other info: Be part of a diverse team committed to equal opportunities and personal development.
- Why this job: Shape the future of AI while mentoring talent and driving impactful projects.
- Qualifications: 10+ years in DevOps or AI/ML, with strong Kubernetes and MLOps expertise.
The predicted salary is between 60000 - 80000 £ per year.
Lenovo is seeking a senior technical leader to guide the strategy, architecture, and delivery of our next generation Hybrid AI Platform. In this role, you will provide leadership across AI infrastructure, MLOps, cloud native platform engineering, and operational excellence – setting direction for teams that build and run production grade AI/ML platforms on Kubernetes. You will drive the vision for scalable, secure, and reliable AI systems while partnering closely with engineering, product, and executive stakeholders. If you are passionate about leading high impact AI platform initiatives, mentoring engineering talent, and shaping enterprise wide Hybrid AI capabilities, we invite you to join us.
Responsibilities
- AI Platform Engineering & Operations
- Provide technical leadership and architectural direction for Kubernetes/OpenShift based AI/ML platform design, scalability strategy, security posture, and operational standards.
- Oversee platform roadmap, ensuring alignment with Lenovo’s broader Hybrid AI strategy and enterprise architecture principles.
- Lead engineering teams in implementing GitOps driven, cloud native platform automation using ArgoCD and Helm.
- Set standards for Linux systems management, platform hardening, and operational reliability across all AI infrastructure.
- MLOps & Model Lifecycle Management
- Define and evolve the enterprise MLOps architecture, enabling reproducible, automated, and governed AI model workflows.
- Lead teams in building and optimizing ML pipelines using Kubeflow Pipelines, Tekton, and Python SDKs.
- Architect scalable, production-ready model serving solutions using KServe, Knative, and Triton (where applicable).
- Champion consistency in model registry usage, metadata management, workflow orchestration, and ML lifecycle governance.
- Automation, Observability & Reliability
- Develop the long‑term automation and platform SRE strategy, including Python/Ansible based automation and Terraform driven IaC patterns.
- Establish observability standards for AI/ML systems using Prometheus, Grafana, AlertManager, and related tooling.
- Oversee capacity planning, performance engineering, incident response processes, and continuous reliability improvements.
- Drive adoption of automation first principles to reduce operational overhead and improve engineering velocity.
- Cloud & Infrastructure Integration
- Own the multi‑cloud and hybrid cloud integration strategy across AWS, GCP, Azure, and on‑premises environments.
- Direct the design of enterprise‑grade identity and security integrations (Azure AD, LDAP, RBAC, secrets management).
- Partner with cloud, security, and networking leadership to ensure the AI platform meets enterprise compliance and governance requirements.
- Collaboration & Customer Success
- Act as a senior point of technical escalation for internal teams and critical customer deployments.
- Influence cross‑functional strategy across AI engineering, DevOps, data science, and product teams.
- Mentor staff engineers and up‑level the team’s capabilities through architectural reviews, technical coaching, and leadership by example.
- Represent the platform’s strategy and progress to leadership stakeholders, ensuring alignment with business goals and customer needs.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
- 10+ years of experience in DevOps, cloud native platform engineering, or AI/ML platform operations, including leadership or architectural responsibility.
- Proven expertise in Kubernetes/OpenShift platform leadership, including cluster lifecycle management, operator design, advanced networking, and platform level security.
- In depth experience with GitOps at scale using ArgoCD, Helm, and automated cluster configuration patterns.
- Advanced knowledge of MLOps tooling (e.g., KServe, Kubeflow, Tekton, Knative) and ML workflow automation.
- Strong proficiency in Python, Bash, and automation frameworks like Ansible and Terraform.
- Deep experience with AWS, GCP, Azure, and hybrid cloud architectural patterns.
- Strong observability leadership experience with Prometheus, Grafana, and distributed system monitoring.
- Exceptional communication, stakeholder management, and cross‑functional leadership skills.
- Proven track record shaping technical strategy, influencing engineering culture, and delivering complex, large‑scale platforms.
Bonus Points
- Experience leading initiatives within the Red Hat OpenShift AI ecosystem.
- Knowledge of enterprise‑scale LLM and model serving architectures (e.g., Triton ensemble models, OCI artifact based LLM deployments).
- Advanced industry certifications such as CKA, CKS, GCP ACE, AWS SAA/SA Pro, or Red Hat OpenShift specializations.
- Experience guiding data engineering or AI/ML workflow orchestration teams.
- Demonstrated leadership in monorepo‑based CI/CD modernization initiatives.
- Experience implementing and governing Internal Developer Portals (e.g., Backstage) across large engineering organizations.
What We Offer
- Opportunities for career advancement and personal development
- Access to a diverse range of training programs
- Performance‑based rewards that celebrate your achievements
- Flexibility with a hybrid work model (3:2) that blends home and office life
- Electric car salary sacrifice scheme
- Life insurance
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.
Sr. AI Infrastructure Engineer employer: Lenovo Careers and Employment
Lenovo is an exceptional employer that fosters a culture of innovation and collaboration, particularly in the vibrant city of Edinburgh. With a strong focus on employee growth, we offer diverse training programmes and performance-based rewards, alongside a flexible hybrid work model that promotes a healthy work-life balance. Join us to lead impactful AI initiatives while mentoring talented engineers in a supportive environment that values diversity and inclusion.
Contact Details:
Lenovo Careers and Employment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Sr. AI Infrastructure Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Lenovo Careers and Employment!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Sr. AI Infrastructure Engineer at Lenovo Careers and Employment.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lenovo Careers and Employment.
✨Apply Directly through Our Website
When you find a suitable opening like Sr. AI Infrastructure Engineer at Lenovo Careers and Employment, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Sr. AI Infrastructure Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Lenovo Careers and Employment, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lenovo Careers and Employment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Lenovo Careers and Employment
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lenovo Careers and Employment!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
