Description and Requirements
This role is open for the Edinburgh, Scotland location only. Candidates must be based there, as the position requires working from the office at least three days per week (3:2 hybrid policy).The Lenovo AI Technology Center (LATC)—Lenovo’s global AI Center of Excellence—is driving our transformation into an AI-first organization. We are assembling a world-class team of researchers, engineers, and innovators to position Lenovo and its customers at the forefront of the generational shift toward AI. Lenovo is one of the world’s leading computing companies, delivering products across the entire technology spectrum, spanning wearables, smartphones (Motorola), laptops (ThinkPad, Yoga), PCs, workstations, servers, and services/solutions. This unmatched breadth gives us a unique canvas for AI innovation, including the ability to rapidly deploy cutting-edge foundation models and to enable flexible, hybrid-cloud, and agentic computing across our full product portfolio. To this end, we are building the next wave of AI core technologies and platforms that leverage and evolve with the fast-moving AI ecosystem, including novel model and agentic orchestration & collaboration across mobile, edge, and cloud resources. This space is evolving fast and so are we. If you’re ready to shape AI at a truly global scale, with products that touch every corner of life and work, there’s no better time to join us.SummaryLenovo is seeking an Advisory AI Software Engineer to help design, build, and evolve LATC’s internal AI Platform - the front door for AI capabilities across Lenovo’s Hybrid AI ecosystem.In this role, you will focus on developer experience, platform usability, and governance by design enabling teams across LATC and CTOO to safely build, evaluate, and operate AI components at scale. Model lifecycle capabilities such as evaluation, provenance, promotion, and runtime integration are delivered as first-class platform features, embedded directly in the developer journey.This role is ideal for a software engineer passionate about building production grade AI platforms and great developer experiences at the intersection of AI, platform engineering, and internal product design.
Responsibilities
AI Platform & Developer Experience
1. Design and evolve the AI Platform as an internal developer platform with repositories, templates, SDKs, and reference implementations.
2. Own the end-to-end developer experience from onboarding and local development through CI/CD, evaluation, and runtime integration.
3. Build SDK first, API-driven interfaces for programmatic access to AI capabilities.
4. Contribute to developer facing services such as portals, inference playgrounds, and evaluation workflows, while centralizing core platform logic.
AI Software & Model Lifecycle
5. Build production grade AI-enabled software using Python, Java, and modern AI frameworks.
6. Embed model lifecycle capabilities including packaging, evaluation hooks, metadata/provenance, and runtime readiness.
7. Support training, fine-tuning, and inference workflows for ML and LLM workloads as part of the platform experience.
CI/CD, Governance & Observability
8. Design and evolve CI/CD pipelines for AI component packaging, testing, and distribution.
9. Implement governance as code patterns, including approval workflows, quality checks, and architectural gates.
10. Embed Open Telemetry based instrumentation for metrics, latency analysis, and evaluation.
11. Define platform standards for versioning, dependency management, and API compatibility.
Cloud, Runtime & Integration
12. Build and deploy platform components on cloud environments (primarily AWS).
13. Integrate with Kubernetes based and hybrid AI runtimes in collaboration with infrastructure teams.
14. Support integration of other LATC and CTOO platforms into the AI ecosystem.
Collaboration & Technical Leadership
15. Collaborate across AI platform, infrastructure, DevOps, research, and partner teams.
16. Contribute to architectural decisions, standards, and long-term platform evolution.
17. Act as a technical steward balancing delivery velocity with safety and maintainability.
Qualifications
Required
18. Bachelor’s degree in Computer Science, Software Engineering, AI, or related field (Master’s or PhD preferred).
19. 8+ years professional experience in software engineering with Python and Java or similar.
20. Experience building developer platforms, SDKs, or internal tools used by other engineers.
21. Hands-on experience delivering ML or AI-enabled systems in production.
22. Solid understanding of ML and deep learning fundamentals.
23. Experience with CI/CD pipelines, automation, and artifact management.
24. Familiarity with cloud platforms (especially AWS) and modern DevOps practices.
25. Strong problems solving skills and effective communication in cross-functional teams.
Bonus
26. Experience with LLMs, agent-based systems, or RLHF.
27. Familiarity with observability tools and OpenTelemetry.
28. Experience with governance-as-code or regulated environments.
29. Knowledge of distributed systems or internal developer portals.
What we offer:
30. Opportunities for career advancement and personal development
31. Access to a diverse range of training programs
32. Performance-based rewards that celebrate your achievements
33. Flexibility with a hybrid work model (3:2) that blends home and office life
34. Electric car salary sacrifice scheme
35. Life insurance
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