Ai engineering director, latc

Description and Requirements

Position Summary Lenovo are building state-or-the-art platform capabilities that will be used in a broad range 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 2 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 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 – 150+ at 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

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