Key skills
PythonGoBashPowerShellAIMLTerraformKubernetesDockerCloudFormationCI/CD
About this role
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
Email: