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Sr. DevOps Engineer-Remote -W2 Role

Cyber Sphere LLC

Remotecontract1 day agosenior
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Title - Sr. DevOps Engineer

Location-Remote

Duration Contract

Job Summary: Senior technical contributor responsible for delivering and governing development-stage DevOps build work for internal-use software and platform components (e.g., CI/CD, infrastructure-as-code, deployment automation) and ensuring release readiness through initial testing evidence and technical artifacts.

Key Responsibilities:
• Design and implement development-stage automation and platform components (coding/configuration) tied to approved scope and milestones.
• Build and maintain CI/CD pipelines and deployment workflows; create reusable templates and standards that support scalable delivery.
• Develop infrastructure-as-code required for new/enhanced application functionality (e.g., environment provisioning, secrets/configuration patterns) and support initial environment validation.
• Establish release quality gates (code review, static checks, initial test evidence) and provide go-live readiness sign-off for defined releases.
• Produce and maintain technical artifacts (ADRs, design notes, runbooks for initial release) and ensure traceability between tasks, code changes, and deliverables.
• Mentor mid-level engineers and coordinate with Product/Architecture on implementation decisions.

Required Qualifications:
• 7+ years of experience in DevOps / Platform Engineering / SRE with hands-on build delivery.
• Strong proficiency with CI/CD tooling and workflow automation.
• Experience authoring and reviewing infrastructure-as-code (e.g., Terraform, CloudFormation, Bicep) and configuration management.
• Proficiency in at least one scripting/programming language used for automation (e.g., Python, Bash, PowerShell).
• Experience implementing secure deployment patterns (secrets management, least privilege, auditability).
• Demonstrated ability to produce technical documentation and delivery artifacts suitable for audit/traceability.Preferred Qualifications:
• Experience supporting AI/ML platforms and data pipelines in production environments.
• Experience with containerization and orchestration (e.g., Docker, Kubernetes) and/or cloud-native deployment patterns.
• Familiarity with regulated or governed environments requiring documentation and change control.

Deliverables / Success Measures: Implemented and documented pipelines/automation aligned to scope; reproducible environment provisioning;

successful completion of initial testing evidence for targeted releases; traceabale artifacts linking tasks - code - test - deployment readiness

Regards,

Sai Srikar

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