Pre-Sales AI Solutions and Services Architect

Description and Requirements

As a Pre- Sales Solutions Architect specializing in Artificial Intelligence (AI) at Lenovo Solutions & Services Group (SSG), you’ll be the driving force behind the strategic direction and implementation of AI solutions for our clients. Your expertise will be instrumental in shaping the future of AI adoption and utilization across industries.

In this role, you will:

• Lead client discussions and engagements, serving as a trusted advisor and thought leader in AI strategy and implementation.
• Collaborate closely with stakeholders to understand their business objectives and translate them into innovative AI strategies and solutions, driving revenue growth and business impact.
• Architect and implement cutting-edge AI solutions tailored to each client’s unique needs, showcasing your expertise in complex AI projects and deals.
• Design and optimize AI deployment strategies across hybrid cloud environments, ensuring seamless operation and maximum efficiency, while also driving revenue through innovative solution offerings.
• Work with internal development teams and partners to manage full lifecycle of AI engagement, leading to value realization for clients.
• Develop frameworks, governance models, and best practices to accelerate AI solution development and ensure successful delivery, establishing yourself as a leader in the AI consulting space.

Basic Qualifications:

• Bachelor’s or master’s degree in a technology / engineering specialization from top institutes.
• experience working in Pre-Sales, consulting or advisory roles, with a focus on AI and emerging technologies.

Preferred Skills:

• Solid knowledge of AI frameworks and libraries, as well as experience across various industries, demonstrating thought leadership and revenue impact.
• Understanding of cloud platforms and security best practices, supported by relevant certifications, driving revenue through innovative solution offerings and practice growth.
• Hands-on experience in full life cycle of AI solution development – Data management (ingestion, integration, transformation), model training & deployment and MLops.