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AI Architect

Lenovomadrid, España

Hace 7 días

Descripción del trabajo

Lenovo Madrid, Community of Madrid, Spain

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Lenovo Madrid, Community of Madrid, Spain

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We are seeking a talented and experienced AI Architect to design, implement, and optimize AI solutions that align with Lenovo’s Hybrid AI vision. In this role, you will collaborate with AI engineers and software developers to create industry-leading AI platforms and solutions. The position requires a good understanding of AI technologies, excellent architecture skills, and the ability to communicate complex technical concepts effectively.

Key Responsibilities :

Design and oversee the architecture development for AI and Generative AI platforms
Create comprehensive AI solutions, including architectures, inference engines, agents, and user interfaces.
Manage the integration of AI solutions into existing systems, including on-premise and edge implementations.
Identify and implement tools, frameworks, and technologies that enhance the effectiveness and efficiency of AI solutions.
Incorporate security measures into AI solutions, focusing on data encryption, access controls, and vulnerability assessments.
Provide guidance and leadership to development teams, ensuring adherence to best practices in AIOps and AI development for both experimental and production environments.
Produce detailed documentation, including system diagrams, data flows, integration points, and technical specifications.
Define and enforce architectural standards, coding guidelines, and best practices across projects & propose innovative implementation strategies.

Qualifications :

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.

Minimum of 5 years in AI architecture design and implementation, with a focus on on-premise or cloud-based AI and Generative AI platforms.

At least 2 years of experience in developing Generative AI architectures , including multi-modal solutions utilizing NVIDIA, OpenAI, cloud-hosted LLMs, or open-source models.

Experience with NVIDIA technologies (e.g., GPUs, CUDA, TensorRT) and integrating tools from NVIDIA AI Enterprise is a plus.

Strong knowledge of on-premise and cloud environments, particularly with containerization and scaling using Kubernetes.

Proven experience in implementing MLOps, LLMOps, or AIOps, and managing CI / CD pipelines for AI deployment using tools such as Jenkins, GitLab, or similar.

Strong programming skills in languages such as Python, React, and scripting languages.

Ability to conduct customer-facing workshops and present to various stakeholders; and working independently or collaboratively with data scientists and AI engineers.

Seniority level

Seniority level Mid-Senior level

Employment type

Employment type Full-time

Job function

Job function Quality Assurance and Information Technology

Industries IT Services and IT Consulting, IT System Custom Software Development, and IT System Data Services

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