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Amazon Madrid Tech Hub is seeking a Senior Technical Program Manager to lead cross-team GenAI programs and align stakeholders across stores and partner tech orgs. You will own roadmaps, drive experiments, and oversee dependencies with engineers and scientists, delivering high-impact solutions.
The role requires deep technical and problem-solving skills, strong communication, and a track record of delivering complex programs in a fast-moving environment.
At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (INTech) leads the enhancement and delivery of Amazon’s state of the art engineering to all the varied customers and cultures of the world.
The team, mainly located in Madrid Technical Hub comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content?
A Sr Technical Program Manager (TPM) will partner with software engineers, applied scientists, Product Managers, and senior management to help create world-class solutions. You will own the cross-team plan for a portfolio of fast-moving GenAI programs: driving roadmap and dependency management, running experiments, and keeping many parallel stakeholders aligned across the stores, partner tech orgs, and multiple regions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product and technical ownership, and want to have fun while they make history. The ideal TPM is a creative, demonstrated leader with analytical abilities and an expeditious drive to deliver results. This opportunity requires deep technical, problem-solving, and communication skills, including the ability to understand ML and GenAI systems well enough to challenge trade-offs with scientists and engineers.