Director, Cloud Platform and AI System Engineering

### **General Information**

Req \#

WD00100901

Career area

Hardware Engineering

Country/Region

India

State

Karnataka

City

BANGALORE

Date

Wednesday, July 15, 2026

Working time

Full\-time

**Additional Locations**

• India \- Karnātaka \- Bangalore
• India \- Karnātaka \- BANGALORE

### **Why Work at Lenovo**

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 \#196 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. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992\) (ADR: LNVGY).

This transformation together with Lenovo’s world\-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

### **Description and Requirements**

Role Overview

The Director, Cloud Platform and AI Engineering, is a senior leadership role responsible for defining, building, and scaling CSW’s Cloud and AI Systems Platform—the foundational technology layer that enables AI and ML capabilities seamlessly across devices, edge, and cloud. This role leads the architecture, delivery, and operation of highly scalable, secure, and high\-performance AI systems that power:

• Predictive and analytical AI products
• Generative AI / LLM / RAG\-based interactive systems
• Telemetry\-driven insights, anomaly detection, and pattern intelligence
• AI developer platforms, MLOps, and model serving infrastructure

The Director ensures the platform enables rapid innovation, operational excellence, and deep integration with Lenovo’s global device ecosystem, supporting Lenovo’s transformation into a software\- and AI\-led business that powers connected, intelligent products across consumer and commercial markets.

As both a technology leader and people leader, this role blends long\-term strategic vision with hands\-on execution. The Director drives architectural direction, engineering governance, talent strategy, and cross\-functional alignment—playing a pivotal role in Lenovo’s AI\-first and cloud\-first transformation.

Key Responsibilities (in order of importance)

1\. Strategic Leadership – Hybrid AI Platform Vision

Define and own the long\-term strategy for CSW’s Hybrid AI Platform across device, edge, and cloud.

Establish the architectural blueprint and multi\-year technology roadmap aligned with Lenovo’s AI\-first business objectives.

Lead engineering strategy for predictive analytics, functional AI, and GenAI\-powered interactive products.

Balance innovation, scalability, cost optimization, and time\-to\-market in platform evolution decisions.

Ensure initiatives deliver measurable impact on customers, products, and revenue.

2\. Technical \& Product Direction

Serve as the senior technical authority for AI systems engineering, overseeing end\-to\-end delivery of:

• Model serving and inference platforms
• GenAI / LLM / RAG pipelines and multi\-agent systems
• High\-throughput data pipelines and analytics engines
• MLOps, observability, and AI developer tooling

Make high\-impact architectural decisions involving LLMs, vector databases, distributed training, inference optimization, and edge intelligence.

Partner with Architecture, Product, and Platform leaders to define system standards, interoperability, and governance models across AI, IoT, and cloud platforms.

3\. Decision\-Making \& Delivery Execution Excellence

Own delivery governance, engineering excellence standards, and success metrics across AI and cloud programs.

Drive prioritization, investment decisions, and resource allocation across a complex, multi\-product portfolio.

Lead cross\-functional decision forums to align business priorities with technical execution.

Ensure secure, reliable, and compliant delivery at scale, across production operations and risk management.

4\. Organizational \& People Leadership

Lead and scale a 40\+ person global organization spanning

Cloud platform engineering

AI/ML systems and MLOps

Data engineering and analytics

IoT and device\-facing platforms

Build leadership layers by coaching architects, tech leads, senior engineers, and managers.

Drive hiring strategy, vendor\-to\-FTE transition planning, and capability development across geographies.

Foster a culture of autonomy, ownership, excellence, and innovation.

Champion structured mentorship, coaching, and AI upskilling initiatives to build long\-term internal capability and retention.

5\. Stakeholder \& Executive Engagement

Act as the strategic liaison across Engineering, Product, Cloud Infrastructure, Security, and Compliance teams.

Represent the AI Systems Engineering organization in executive forums and architecture boards.

Communicate platform strategy, delivery progress, ROI, and risk transparently to senior leadership.

Advocate for scalable, ethical, and responsible AI adoption across Lenovo’s software and device portfolio.

Scope \& Impact

This role has enterprise\-wide impact across CSW and Lenovo’s broader product ecosystem.

Key outcomes include

Customer Experience: 15–20% CSAT/NPS improvement via resilient AI services and sustained 99\.9% uptime

Product Acceleration: 30–40% faster AI feature release cycles; 2–3× increase in AI feature adoption

Revenue Enablement: Faster monetization of AI through predictive analytics, insights, and subscription\-based services

Quality \& Compliance: Strong governance aligned with GDPR, CCPA, and responsible AI standards

Workforce Productivity: 15–25% gain in developer productivity and improved retention of top technical talent.

Organization \& Reporting

The Director leads a senior leadership bench, including

Senior Manager, Cloud Services

Senior Manager, Hybrid AI Platform Engineering

AI Systems Architect

Delivery Manager

The role carries full accountability for organizational design, talent strategy, engineering excellence, and delivery execution across a rapidly growing global team.

Required Qualifications

Technical \& Domain Expertise

12\+ years of experience in software engineering, cloud platforms, or distributed systems, with senior leadership responsibility

Deep expertise in cloud\-native architecture, distributed systems, and platform engineering

Proven experience delivering global, fault\-tolerant platforms (e.g., 300M\+ events/day, 99\.9% uptime)

Strong understanding of AI/ML systems, including

Model lifecycle management and MLOps

High\-throughput data engineering and analytics platforms

Model serving, inference optimization, and observability

Experience operating multi\-tenant, enterprise\-grade platforms across cloud and on\-prem environments

Leadership \& Execution

Proven experience leading large, global engineering organizations (30\+ engineers) across multiple domains

Track record of building high\-performing teams and strong leadership pipelines

Experience managing multiple teams across platforms, IoT, data, and product experiences

Strong decision\-making capability in complex, ambiguous, and high\-scale environments

Demonstrated ability to drive cross\-functional alignment across engineering, product, infrastructure, and security

Business \& Strategic Acumen

Ability to translate business strategy into executable technology and platform roadmaps

Strong financial and operational judgment, including cost optimization and ROI\-driven investment decisions

Executive\-level communication skills with the ability to influence senior leadership and enterprise stakeholders.

Preferred Qualifications

Experience with hybrid or device\-to\-cloud platforms at a global scale

Background in DevSecOps, cloud governance, and platform cost optimization

Exposure to enterprise AI governance, security, and compliance frameworks

Innovation leadership demonstrated through GenAI / multi\-agent systems, patents, publications, or industry conference participation.

**Additional Locations**

• India \- Karnātaka \- Bangalore
• India \- Karnātaka \- BANGALORE
• India
• India \- Karnātaka

\* India \- Karnātaka \- Bangalore , \* India \- Karnātaka \- BANGALORE

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