Senior DevOps / MLOps Engineer
$160,000–$190,000 year
RemoteUnited States
Job Summary
Deploy and operate the Azure platform end-to-end, managing AKS, networking, identity, and storage environments from development through production. Own infrastructure as code to ensure reproducibility and detect drift, while hardening access controls with least privilege and secrets management. Operate the AI infrastructure layer including self-hosted observability, telemetry, and model gateways, and partner with AI Operations on deploy-and-release paths using Octopus Deploy. Build platform reliability through monitoring, alerting, and incident response, and manage cloud and AI costs via metering, budgets, and active remediation strategies.
Required Qualifications
- 5+ years in DevOps, platform engineering, or site reliability engineering in SaaS environments
- Deep Azure experience: AKS, networking, identity (Entra), and monitoring; you have run production Kubernetes
- Infrastructure as code as your default (Terraform, Bicep, or similar), plus strong scripting; you automate before you document
- MLOps experience: deploying and operating LLM or ML systems in production, including model gateways, inference infrastructure, or AI observability stacks
- Demonstrated cost work: you can point to cloud spend you found, explained, and reduced
- Experience in compliance-heavy environments (FedRAMP, StateRAMP, SOC 2, or similar) is a strong plus
- Comfortable holding production access, with the discipline that implies
Desired Qualifications
- Experience in compliance-heavy environments (FedRAMP, StateRAMP, SOC 2, or similar)
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