Level

Amazon

Software Development Engineer II, AWS SageMaker

Amazon is hiring a Software Development Engineer II, AWS SageMaker in Bellevue, United States. It pays $144k-$194k a year and Level rates it ; you can apply on Level.

AI in this role

Software Development Engineer for AWS SageMaker AI, building core governance, lineage, and catalog platforms for machine learning assets.

sagemakeraws
machine-learningsoftware-developmentcloud-computinggovernance
Are you a highly skilled and innovative SDE with a passion for developing new machine learning capabilities and driving innovation to build customer-centric solutions in Amazon SageMaker AI? Are you interested to play a key role in developing software applications at AWS? We invite you to join us and be part of making history.

The Amazon SageMaker Governance team is seeking Software Development Engineer to join our organization. SageMaker Governance provides the foundational platform capabilities that give enterprise customers trust, visibility, and control over their ML assets at scale. These capabilities enable customers to discover, audit, and manage machine learning models and workflows across accounts and organizations through a unified catalog, version-controlled lifecycle management, and end-to-end lineage tracking.


Engineers on the Amazon SageMaker Governance team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure SageMaker remains a best-in-class service. You will be held to the highest standards of engineering and operational excellence, including building highly resilient and scalable systems, producing clear and effective technical documentation, actively contributing to discussions on strategic direction, and continuously raising the bar. Most importantly, you will have the opportunity to collaborate with a team of highly skilled and dedicated engineers who share a commitment to achieving new levels of success.

About Amazon SageMaker AI

Amazon SageMaker AI is a fully managed machine learning service that simplifies the process of building, training, and deploying machine learning models. It abstracts away the undifferentiated heavy-lifting associated with large-scale machine learning implementations, allowing developers and data scientists to focus on the core modeling and problem-solving aspects of their work. SageMaker is currently utilized by businesses of all sizes, including some of the world's leading enterprises, across a growing number of geographic regions.


About the team

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.



Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Key job responsibilities
**System Design & Delivery** – Own end-to-end delivery of large-scale distributed services with high availability, low latency, and operational excellence.
**Cross-Team Influence** – Collaborate with product, science, and partner engineering teams to define roadmaps and deliver customer-obsessed solutions.
**Operational Excellence** – Champion best practices in CI/CD, observability, testing, and incident management. Drive a culture of ownership and accountability.
**Innovation** – Identify opportunities to simplify, automate, and improve the developer experience. Contribute to patents, publications, or open-source projects where appropriate.
**Customer Obsession** – Deeply understand customer workflows and pain points; translate insights into scalable, intuitive platform capabilities.

Basic qualifications

- 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

Preferred qualifications

- 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, BELLEVUE - 143,700.00 - 194,400.00 USD annually

How we rate this

Software Development Engineer II, AWS SageMaker at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningSoftware DevelopmentCloud ComputingGovernanceSagemakerAWS

Also common in software engineer jobs at this level

Pay

This job starts at
$144k
Typical software engineer job
$168k

This posting starts 14% below the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where software development was part of your work. What did you do?
  3. Tell me about a project where cloud computing was part of your work. What did you do?
  4. Tell me about a project where governance was part of your work. What did you do?
  5. Walk me through how you've used Sagemaker in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Machine learning, Software Development, Cloud Computing, Governance, and Sagemaker. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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