Sr. Azure Platform & Reliability Engineer

Mondo

Saint Louis, MO
Today

$70–$80 Per Hour

Highlights

Strong observability experience across metrics, logs, traces, alerting, dashboards, and service health monitoring using tools such as Datadog, Azure Monitor, OpenTelemetry, or Application Insights. Minimum Requirements: 7 years of experience in site reliability engineering, platform engineering, cloud infrastructure, or a closely related technical role.

Numbers & Facts

Location	Saint Louis, MO
Salary	$70–$80 Per Hour

Description

Job Description

Apply now: Senior Azure Platform & Reliability Engineer, Onsite - St. Louis, MO. Start date is ASAP for this 6-Month Contract-to-Hire position. Job Title: Senior Azure Platform & Reliability Engineer Location-Type: Onsite, St. Louis, MO Start Date: ASAP (approximately 2 weeks from offer) Duration: 6 Month Contract-to-Hire Compensation Range: $70-$80/hr Benefits: Eligible for Health, Dental, Vision, and 401K Visa Sponsorship: Not eligible for visa sponsorship Job Description:
This senior individual contributor role embeds directly with the client's cloud platform and engineering teams to assess, improve, and sustain the reliability, observability, and operational readiness of the organization's most critical Azure-hosted systems.
Job Summary
Assess critical enterprise applications against internal reliability standards, identifying gaps in monitoring, metrics, logging, alerting, and recovery.
Partner with application, cloud, infrastructure, and operations teams to design and implement systemic reliability improvements across production environments.
Use incident history and root cause analysis findings to identify recurring issues and drive corrective and preventative solutions.
Implement hands-on fixes and improvements directly within Azure, including Kubernetes, identity, networking, observability tooling, and infrastructure-as-code.
Build and maintain runbooks, dashboards, alert standards, and reusable reliability guidance to enable owning teams after each reliability mission.
Design and implement automation-first solutions that reduce toil, improve deployment safety, and strengthen observability across metrics, logs, and traces.
Champion responsible use of AI-assisted engineering tools to accelerate reliability improvements, incident analysis, documentation, and automation.
Minimum Requirements:
7 years of experience in site reliability engineering, platform engineering, cloud infrastructure, or a closely related technical role
Bachelor's degree in computer science, engineering, information technology, or equivalent practical experience.
Hands-on Azure experience with broad, end-to-end knowledge of managed services, identity, networking, monitoring, and operational practices.
Kubernetes experience, with AKS strongly preferred, including containerized runtimes and enterprise hosting patterns.
Experience with infrastructure-as-code, preferably Terraform, and scripting in at least one language such as Python, PowerShell, or Bash.
Demonstrated experience entering unfamiliar production systems, assessing reliability risks, and personally implementing improvements end to end.
Active, practical experience using and championing AI-assisted engineering tools such as GitHub Copilot and OpenAI Codex.
Preferred Qualifications:
Experience with SLOs, SLIs, error budgets, production readiness reviews, resilience testing, or formal incident learning programs.
Hands-on experience with Azure Kubernetes Service, Azure Container Registry, Azure Key Vault, Azure Monitor, managed identities, or Azure Policy.
Experience with GitHub Enterprise workflows, including branch protection, CODEOWNERS, dependency scanning, GitOps, Helm, or Kustomize.
Background in software engineering or system design, with progression into cloud, platform, or SRE-focused roles.
Prior experience in smaller or midsize organizations, lean cloud teams, central platform teams, or consulting environments where broad ownership was required.
Experience with chaos or resilience testing, FinOps practices, or cloud operating model design.
Strong observability experience across metrics, logs, traces, alerting, dashboards, and service health monitoring using tools such as Datadog, Azure Monitor, OpenTelemetry, or Application Insights.