AI Engineering Director, LATC

Lenovo; Greater London; Hybrid; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Opportunities for career advancement

Access to a range of training programs

Performance-based rewards

Hybrid work model

Electric car salary sacrifice scheme

Life insurance

Job summary

Lenovo is looking for a leader in AI engineering to shape and execute the architecture of their AI strategy across sites in London and Edinburgh. This role will involve architecting components for intelligent AI deployment while mentoring a growing engineering team.

The ideal candidate will have over 8 years of experience in data engineering or AI/ML, with a strong background in distributed systems. Lenovo offers a hybrid work model and opportunities for career advancement and personal development.

Qualifications

• 8+ years in Data, AI/ML engineering, distributed systems, or orchestration platform development.
• Proven experience in scaling multi-model and multi-tenant inference systems.
• Expertise in designing systems balancing throughput, latency, and cost.

Responsibilities

• Architect and lead engineering delivery of key components including Data and Infrastructure.
• Collaborate with university researchers on algorithmic innovation.
• Direct and mentor an engineering team to foster a culture of excellence.

Skills

Data engineering

AI/ML engineering

Distributed systems

Orchestration platform development

Scalability

Latency Cost Optimization

API integration

Education

Graduate degree (MS/PhD) in Computer Science, AI/ML, Distributed Systems, or related discipline

Tools

API tools

Job description

Position Summary

Lenovo are building state‑of‑the‑art platform capabilities that will be used in a broad range of scenarios from personal and enterprise use cases. These components will help power future capabilities on devices including wearables to autonomous robots working in deep sea environments.

Lenovo don’t just do AI on the cloud, instead orchestrating and routing workloads intelligently across devices, laptops, and cloud environments — optimizing for cost, privacy, latency, and user experience.

This role is leading the engineering across our two LATC sites, Imperial College London and Edinburgh, where you will not only shape the architecture, roadmap, and execution of Lenovo’s AI strategy, but also play a founding leadership role in establishing and growing the sites. This unique opportunity blends high‑impact product delivery with cutting‑edge R&D and cross‑disciplinary collaboration with world‑class academic researchers.

You will ensure our platform becomes a global benchmark for intelligent AI deployment while helping build Lenovo as a vibrant new hub for AI innovation in the UK.

Key Responsibilities

• Architect and lead the engineering delivery of key LATC components including Data, Context and Memory, Infrastructure (traditional and ML training), Observability, Operations and Run, Evaluation (Model and end‑to‑end stack) and the business‑facing AI portal (HIVE).
• Collaborate closely with university researchers to accelerate algorithmic innovation, federated learning capabilities, and privacy‑preserving AI deployment.
• Direct and mentor a high‑caliber engineering team that plans to grow from 30 to 150+ at a controlled yet high pace, fostering a culture of technical excellence, rapid prototyping, and rigorous validation.
• Drive integration of LATC capabilities into Lenovo’s consumer and enterprise products, in partnership with internal product and platform engineering teams.
• Stay ahead of emerging trends in distributed AI, multi‑agent orchestration, and edge‑to‑cloud integration, guiding Lenovo’s long‑term technical direction.

Required Qualifications

• 8+ years in Data, AI/ML engineering, distributed systems, or orchestration platform development in a research or production environment. At least 3 years working on AI/ML workloads.
• Scalability: Proven experience in scaling multi‑model and multi‑tenant inference systems to millions of daily requests.
• Latency Cost Optimization: Expertise in designing systems that balance throughput, latency, and cost per query.
• Experimentation Platforms: Familiarity with A/B testing, reinforcement learning from feedback, and dynamic policy evaluation for routing decisions.
• Tool API Integration: Proficiency in integrating external APIs, tools, and databases into orchestration pipelines.
• Observability: Ability to design monitoring systems for correctness, drift detection, and performance regressions across model families.
• Strong leadership track record with the ability to translate research into deployed systems.

Preferred Qualifications

• Experience collaborating with academic research institutions or research‑led industry programs.
• Prior work in AI workload optimization for consumer electronics, IoT devices, or edge platforms.
• Graduate degree (MS/PhD) in Computer Science, AI/ML, Distributed Systems, or related discipline.
• Familiarity with federated learning, agent‑based orchestration, and privacy‑preserving AI frameworks.
• Strong ability to operate across ambiguous and emerging technology landscapes, defining scalable frameworks for innovation.

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.