Senior AWS Cloud Engineer
JOB_53360901178021Job type
PermanentLocation
SeattleProfession
CloudIndustry
Technology & Internet ServicesPay
180k
Sr. AWS Cloud Engineer
Senior AWS Cloud Engineer
Location:
Hybrid – Seattle, WA or Pembroke Pines, FL
Hybrid – Seattle, WA or Pembroke Pines, FL
Employment Type:
Permanent Full-Time
Permanent Full-Time
Compensation:
$180K base + 10–20% annual bonus (equity available, not disclosed)
$180K base + 10–20% annual bonus (equity available, not disclosed)
Relocation Assistance:
Available
Available
Note: I am not accepting submissions from agencies, contract-to-contract arrangements, or third-party recruiters (R2R). Direct applicants only.
Top Skills / Requirements
- Proven ability to design and manage scalable compute environments using AWS EC2 and Lambda.
- Hands-on experience with container orchestration and infrastructure automation using Docker, Kubernetes, and CI/CD workflows.
- Strong background in cloud networking, storage architecture, and security best practices.
- Experience deploying machine learning models in cloud environments, with proficiency in services like AWS SageMaker.
- Solid understanding of ECS, with preference for candidates who have worked with AWS Fargate in production.
- Familiarity with integrating ML models into scalable software systems and optimizing performance in live environments.
- 7–10 years of experience in AWS cloud engineering, ideally within complex enterprise settings or directly at Amazon.
- Exposure to robotics engineering or work related to Amazon Prime Air is highly desirable.
- Skilled in building data-intensive cloud architectures that support high-throughput and large-scale processing.
- Proficient in Python, Java, or JavaScript for cloud-native development and automation.
- Experience with cloud compliance, governance, and secure deployment practices.
- Advanced degree (Master’s preferred) in Mechanical Engineering or a related STEM discipline.
Job Description
A stealth-mode technology company is developing a next-generation platform focused on enhancing human capabilities through advanced cloud and machine learning systems. This role involves architecting scalable AWS infrastructure, deploying ML models, and supporting high-performance applications in areas such as robotics, spatial computing, and artificial intelligence.
Responsibilities
Infrastructure Operations
Maintain and enhance cloud infrastructure through upgrades, patching, and performance tuning.
System Reliability & Troubleshooting
Identify and resolve issues across ML pipelines, cloud services, and system integrations to ensure high availability.
ML Deployment & Integration
Support the rollout of production-grade ML models across AWS, Azure, or GCP platforms. Build and maintain pipelines that handle large-scale data workflows and integrate seamlessly with existing systems.
Performance Monitoring
Track and analyze system and model performance metrics to proactively address bottlenecks and inefficiencies.
Security & Compliance
Ensure all cloud systems meet regulatory and security standards, especially when handling sensitive or mission-critical data.
Collaboration & Engineering Support
Work alongside cross-functional teams to deploy, monitor, and scale ML operations and cloud services.
Documentation & Mentorship
Create and maintain technical documentation, share insights with peers, and contribute to team development through mentorship and collaboration.
Innovation & Learning
Stay informed on emerging cloud and ML technologies, evaluate new tools, and help drive continuous improvement across platforms.
Knowledge, Skills & Abilities (KSAs)
Knowledge
- Experience with AWS and other cloud platforms (Azure, GCP) in professional environments.
- Strong foundation in designing cloud systems for data-intensive workloads.
- Familiarity with containerization and automated deployment tools.
- Understanding of cloud networking, storage, and security protocols.
Skills
- Hands-on with ML services like AWS SageMaker, Azure ML, or Google AI Platform.
- Skilled in CI/CD pipeline development for ML deployment.
- Capable of building scalable software and integrating ML models into production systems.
- Proficient in Python, Java, or JavaScript.
Abilities
- Able to work independently within large, cross-functional teams.
- Strong communicator with technical and non-technical audiences.
- Adaptable to fast-changing project requirements and business needs.
- Committed to maintaining high standards in code quality, system performance, and design.
- Excellent analytical and problem-solving capabilities.
Note: I am not accepting submissions from agencies, contract-to-contract arrangements, or third-party recruiters (R2R). Direct applicants only.
#LI-DNI
Senior AWS Cloud EngineerJOB_533609011780212025-08-072025-11-05
Talk to Aldo Cabral, the specialist consultant managing this position
Located in Raleigh, 2840 Plaza Place, Suite 340Telephone: 18133212538JOB_53360901178021