> Markdown version of [/jobs/ext/4013083-sr-software-development-manager-compute-ai-services](https://www.wearedevelopers.com/jobs/ext/4013083-sr-software-development-manager-compute-ai-services). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Software Development Manager, Compute AI Services - **Company:** Amazon.com, Inc. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $253,100.0 - $342,300.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Amazon Web Services, Data Cleansing, Machine Learning, Software Engineering, Graphics Processing Unit (GPU), AI Platforms, Machine Learning Operations - **Published:** October 29, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28144553/Sr-Software-Development-Manager-Compute-Ai-Services-California-Santa-Clara-7375 ## About the Role 10+ years of engineering experience - 5+ years of engineering team management experience - 10+ years of planning, designing, developing and delivering consumer software experience - Experience partnering with product or program management teams - Experience managing multiple concurrent programs, projects and development teams in an Agile environment Preferred Qualifications - Experience partnering with product and program management teams - Experience designing and developing large scale, high-traffic applications ## Description Amazon SageMaker is a fully managed machine learning platform that enables developers and data scientists to build, train, tune, and deploy ML models at scale. SageMaker removes the heavy lifting from each step of the machine learning workflow, making it easy to develop high-quality models with broad framework support, built-in algorithms, and one-click deployment. Amazon SageMaker is designed to democratize machine learning by providing a comprehensive set of tools spanning data preparation, model development, training infrastructure, experiment tracking, model hosting, MLOps automation, and responsible AI governance. The platform scales seamlessly from single-node experimentation to distributed training across thousands of GPUs, and from real-time inference to cost-efficient batch and asynchronous endpoints. SageMaker integrates deeply with the AWS ecosystem to deliver enterprise-grade security, compliance, and reliability for production ML workloads. As Director of Engineering for Amazon SageMaker, you will be responsible for leading a group of top talent in the design and development of next-generation machine learning infrastructure and platform services on AWS. You'll also own the business strategy and roadmap for the service and will be responsible for all aspects of its end-to-end engineering and growth.