Remote Active Hiring 1 month ago

Senior DevOps Engineer

M

Micro1

Remote • Other

Salary Range

$30 - $130/hour

Experience

N/A

Location

Remote

Job Type

Remote

Required Skills

Kubernetes Aws Gcp Python

Description

Job Title: Senior DevOps Engineer


Job Type: Contractor


Location: Remote


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Design, implement, and maintain scalable infrastructure solutions using Kubernetes across AWS and GCP environments.
  2. Develop, manage, and optimize CI/CD pipelines to ensure seamless integration and continuous delivery for diverse applications.
  3. Automate infrastructure management, monitoring, and deployments with Python and DevOps best practices.
  4. Collaborate closely with cross-functional teams to support robust cloud-native architectures and application reliability.
  5. Monitor system performance, troubleshoot issues, and implement proactive solutions for optimization and security.
  6. Document processes, architectures, and solutions clearly for technical and non-technical audiences.
  7. Champion a culture of transparent communication and knowledge sharing within the customer's team.


Required Skills and Qualifications:

  1. Expertise in Kubernetes orchestration and management of containerized applications.
  2. Hands-on experience with both AWS and GCP cloud platforms.
  3. Proven ability to develop automation scripts and tools using Python.
  4. Deep understanding of infrastructure-as-code, CI/CD pipelines, and DevOps principles.
  5. Excellent written and verbal communication skills and a collaborative mindset.
  6. Experience with monitoring, logging, and proactive system management.
  7. Strong problem-solving abilities in complex, distributed cloud environments.


Preferred Qualifications:

  1. Certifications related to Kubernetes, AWS, or GCP.
  2. Prior work in AI/ML infrastructure or data-intensive environments.
  3. Familiarity with additional programming languages or automation frameworks.

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