> Markdown version of [/jobs/ext/1933264-software-development-engineer-ii-aws-sagemaker-ai](https://www.wearedevelopers.com/jobs/ext/1933264-software-development-engineer-ii-aws-sagemaker-ai). 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). --- # Software Development Engineer II, AWS SageMaker AI - **Company:** Amazon.com, Inc. - **Location:** Bellevue, WA, United States - **Salary:** $143,700.0 - $194,400.0 - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Software Applications, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Code Review, Computer Programming, Data Cleansing, Software Design Patterns, Distributed Systems, Perl (Programming Language), Fault Tolerance, Machine Learning, Object-Oriented Software Development, Service-Oriented Architecture, Software Engineering, AWS Cdk, Data Logging, Multithreading, Graphics Processing Unit (GPU), Pytorch, Backend, Cloudformation, Kubernetes, Information Technology, Build Process, Slurm, Software Coding, Software Version Control, Programming Languages - **Published:** August 5, 2026 - **Apply:** https://www.amazon.jobs/en/jobs/10492392/software-development-engineer-ii-aws-sagemaker-ai ## About the Role A successful candidate has a strong software-engineering foundation, writes high-quality distributed-systems and services code, communicates clearly, and is motivated to deliver results in a fast-paced, ambiguous environment., 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - Experience programming with at least one software programming language, 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent - - Experience with workflow/pipeline orchestration (Airflow, Step Functions, or similar) and event-driven or service-oriented architectures. - - Experience with container and cluster compute (Kubernetes/EKS, Ray, Slurm, AWS Batch) and cloud infrastructure-as-code (AWS CDK/CloudFormation). - - Experience building and operating fully-managed cloud services at scale, including resiliency, checkpointing, and fault tolerance for long-running jobs. - - Familiarity with machine-learning / deep-learning training workflows, GPU/accelerator compute (SageMaker HyperPod, AWS Trainium, P5-class GPUs), or distributed-training frameworks (PyTorch FSDP, Megatron-LM, DeepSpeed, verl). ## Description We're looking for a Software Development Engineer to help design, build, and operate the distributed systems at the core of this platform - the orchestration engine, compute integrations, SDK and contract layer, and the infrastructure that runs large-scale training and customization jobs. You'll own components end-to-end, from design through delivery and on-call operations, and work closely with the ML scientists and platform teams who depend on Model Factory every day. You'll turn requirements into robust, scalable, supportable services that fit cleanly into the overall architecture, uphold a high engineering bar, and grow your scope and technical leadership as you go., As a Software Development Engineer on the SageMaker AI team, you will: - Design, build, test, and operate services that orchestrate foundation-model data preparation, training, evaluation, and deployment as reliable, contract-validated workflows. - Own delivery of individual components end-to-end - from design and implementation through deployment, monitoring, and on-call operations. - Build and extend compute-backend integrations and job launchers - submitting, monitoring, and recovering large-scale training jobs across SageMaker (Training/Processing/HyperPod), EMR, AWS Batch, and Kubernetes/EKS. - Improve the platform's resiliency and operability for long-running distributed jobs - checkpoint/resume, fault detection and recovery, retries, and observability (metrics, logging, experiment tracking). - Contribute to the SDK, workflow orchestration, and schema/contract layer that teams use to declare and run jobs, and to the CDK infrastructure that deploys the platform. - Integrate containerized training and evaluation frameworks (e.g., PyTorch/FSDP, verl, NeMo/Megatron) into the platform's task and recipe model. - Contribute to design and architecture discussions, write clear technical designs, and uphold engineering best practices (code review, testing, operational readiness). - Collaborate with ML scientists and internal customers to translate training requirements into reliable, self-service platform capabilities, and help onboard and mentor interns and new engineers as you grow. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Machine Learning for Software Developers (and Knitters)](https://www.wearedevelopers.com/videos/154-machine-learning-for-software-developers-and-knitters) - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best Countries for Software Engineers](https://www.wearedevelopers.com/magazine/267-best-countries-for-software-engineers) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers)