Cloud AI Productivity Engineer

hace 13 horas


Madrid, Madrid, España Amazon A tiempo completo

At Amazon, we're revolutionizing workplace productivity with innovative generative AI technology. Our cutting-edge AI-powered assistant transforms how enterprises operate by empowering employees to be more creative, data-driven, efficient, prepared, and productive.

Unlike traditional AI assistants, Amazon Q Business leverages advanced artificial intelligence to answer questions, provide summaries, generate content, and securely complete tasks based on enterprise data. Central to its functionality is the ability to unify disparate data sources across organizations. With over 40 secure connectors to popular enterprise applications and document repositories, it offers a seamless search experience that breaks down information silos and enhances collaboration.

Amazon Q Apps allows employees to quickly create and share generative AI-powered applications, fostering a culture of innovation within the workplace. As a Cloud AI Productivity Engineer, you will play a vital role in designing, developing, and optimizing the platform's core components. Your work will ensure high performance, scalability, and reliability while directly impacting how businesses leverage AI for enhanced operations and data-driven decision-making.

**Key Responsibilities:**
* Design and develop core components of the platform
* Ensure high performance, scalability, and reliability
* Collaborate with cross-functional teams to deliver high-quality products
* Stay up-to-date with industry trends and emerging technologies

**Requirements:**
* 3+ years of professional software development experience
* Experience with cloud-based systems and AWS services
* Strong understanding of artificial intelligence and machine learning concepts
* Bachelor's degree in computer science or equivalent

We offer a competitive salary range of $**180,000 - $250,000** per year, depending on your location and qualifications. Join us in shaping the future of work with Amazon and contribute to making significant strides in the generative AI landscape for enterprise productivity.


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