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Browse remote AWS positions at AI companies — SageMaker ML platform engineering, cloud AI infrastructure, and MLOps on AWS.
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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Posted 4 days ago
Software Engineering Manager (Agentic Engineering, US Eastern)
Coder
United States
As an Engineering Manager on Coder’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development...
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We are looking for a Senior Solutions Engineer, Federal/Public Sector to join our Solutions Engineering team. You will partner with Account Executives...
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CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million c...
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We are looking for a Senior Solutions Engineer to join our Sales Engineering team. You will partner with Account Executives to qualify, progress, and...
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Posted 4 days ago
Staff+ Software Engineer, Deployment
Anthropic
Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society...
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We are looking for a Senior Solutions Engineer to join our Sales Engineering team. You will partner with Account Executives to qualify, progress, and...
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Role guide
What to expect in remote AWS jobs
AWS is the most widely used cloud platform for AI companies. Remote AWS jobs in this space combine cloud engineering with ML infrastructure knowledge — SageMaker for model training and deployment, S3 and Glue for data pipelines, and Lambda or ECS for serving. Engineers who bridge cloud architecture and ML system design are consistently in demand.
What you'll work on
- Deploy and monitor ML models using SageMaker endpoints and pipelines
- Build scalable data ingestion and processing pipelines with S3 and Glue
- Design cost-efficient ML training infrastructure on EC2 GPU instances
- Create serverless AI feature APIs using Lambda and API Gateway
What companies look for
- SageMaker experience — training jobs, endpoints, and pipelines
- Strong AWS fundamentals — IAM, VPC, S3, EC2, ECS, Lambda
- Infrastructure-as-code with Terraform or CDK
Frequently asked questions
What AWS jobs are available remotely at AI companies?
Cloud engineering roles focused on ML infrastructure — SageMaker pipelines, data lake architecture on S3, and AI service integration. Many also involve ECS or EKS for container orchestration.
Do remote AWS AI jobs require SageMaker experience?
For ML-focused roles, SageMaker experience is a strong advantage. General cloud engineering roles may focus on ECS/EKS, Lambda, or data services instead. Check listings for the specific service stack.
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