Senior MLOps / DevOps Engineer - remote
Summary:
Provide end to end reliability ownership across infrastructure, CI/CD, and monitoring systems.
Responsibilities
Operate and maintain Azure infrastructure and Kubernetes based deployments.
Design, build, and manage CI/CD pipelines, including environment promotion and release workflows.
Centralize observability across logging, metrics, and tracing; define and enforce SLOs and alerting standards.
Implement and maintain security controls, including secrets management, container image scanning, RBAC, and audit logging. Required Qualifications
5 9 years of experience in DevOps, SRE, or MLOps roles with strong expertise in Docker, Kubernetes, and Azure.
Hands on experience with infrastructure as code, CI/CD automation, and monitoring/alerting platforms.
Proven experience supporting Python based services and machine learning workloads in production environments. Preferred Qualifications
Experience with MLflow, feature flag frameworks, blue/green or canary deployments, and cloud cost?management dashboards. Additional Responsibilities
Provide L2/L3 production support for the Network AI Platform, including incident triage, defect resolution, hotfixes, minor enhancements, release hygiene, and change requests.
Maintain guardrails and model quality by managing prompt and configuration changes, tuning retrieval, and performing evaluation and regression checks prior to releases.
Ensure stability and reliability of integrations (e.g., ServiceNow, Splunk, SharePoint, internal knowledge bases) by maintaining schemas, credentials, and SLAs.
Drive observability and operational excellence through dashboards and alerts for pipelines, APIs, models, and workers; author incident runbooks and lead post?mortems.
Enforce secure SDLC practices, including secrets management, least privilege access, audit logging, and dependency/CVE hygiene.
Produce and maintain clear documentation and handover materials, including up to date runbooks, how to playbooks, and environment diagrams.
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Apply To this Job
Provide end to end reliability ownership across infrastructure, CI/CD, and monitoring systems.
Responsibilities
Operate and maintain Azure infrastructure and Kubernetes based deployments.
Design, build, and manage CI/CD pipelines, including environment promotion and release workflows.
Centralize observability across logging, metrics, and tracing; define and enforce SLOs and alerting standards.
Implement and maintain security controls, including secrets management, container image scanning, RBAC, and audit logging. Required Qualifications
5 9 years of experience in DevOps, SRE, or MLOps roles with strong expertise in Docker, Kubernetes, and Azure.
Hands on experience with infrastructure as code, CI/CD automation, and monitoring/alerting platforms.
Proven experience supporting Python based services and machine learning workloads in production environments. Preferred Qualifications
Experience with MLflow, feature flag frameworks, blue/green or canary deployments, and cloud cost?management dashboards. Additional Responsibilities
Provide L2/L3 production support for the Network AI Platform, including incident triage, defect resolution, hotfixes, minor enhancements, release hygiene, and change requests.
Maintain guardrails and model quality by managing prompt and configuration changes, tuning retrieval, and performing evaluation and regression checks prior to releases.
Ensure stability and reliability of integrations (e.g., ServiceNow, Splunk, SharePoint, internal knowledge bases) by maintaining schemas, credentials, and SLAs.
Drive observability and operational excellence through dashboards and alerts for pipelines, APIs, models, and workers; author incident runbooks and lead post?mortems.
Enforce secure SDLC practices, including secrets management, least privilege access, audit logging, and dependency/CVE hygiene.
Produce and maintain clear documentation and handover materials, including up to date runbooks, how to playbooks, and environment diagrams.
Apply tot his job
Apply To this Job