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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.
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