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Observability Engineer

Dale Workforce SolutionsUnited States🇺🇸United StatesPosted Oct 12, 2026

Why This Role Stands Out

This hybrid Observability Engineer role at Dale Workforce Solutions offers a fantastic opportunity to shape critical cloud platform capabilities and drive operational excellence using cutting-edge DevOps practices. You'll thrive here if you have a strong background in AWS, CI/CD, and automation, and are eager to enhance developer productivity and system reliability. Apply today to contribute to a dynamic and forward-thinking engineering environment!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
23 hours ago

Job Description

Summary:
Builds and operates the cloud platform, automation, and delivery capabilities that enable teams to develop, deploy, and run secure, reliable, and scalable solutions. Ensures operational excellence through strong DevOps practices, while supporting observability, governance, compliance, and AI oversight requirements.

Key Responsibilities

  • Build and maintain CI/CD pipelines, cloud infrastructure, and platform automation.
  • Automate environment provisioning, deployments, monitoring, and operational processes.
  • Support production operations, incident management, root cause analysis, and reliability engineering.
  • Implement platform security, DevSecOps controls, and compliance automation.
  • Partner with engineering teams on production readiness, resiliency, and operational best practices.
  • Establish reusable platform capabilities that improve developer productivity and operational consistency

Required Qualifications

  • AWS cloud engineering and infrastructure-as-code experience.
  • Strong CI/CD, automation, DevOps, and platform engineering background.
  • Experience with containers, APIs, distributed systems, and modern software delivery practices.
  • Scripting and automation skills (Python, Bash, PowerShell, or similar).

Preferred Qualifications

  • Observability platforms such as CloudWatch, OpenTelemetry, Datadog, Grafana, Prometheus, or Splunk.
  • Governance automation, policy-as-code, auditability, and compliance controls.
  • Security telemetry, DevSecOps, and regulated industry experience.
  • AI governance, model monitoring, and agent/LLM observability.

Differentiators

  • Uses automation to balance speed, reliability, and governance.
  • Strong focus on observability, operational excellence, and platform enablement.
  • Comfortable supporting both traditional applications and emerging AI-enabled solutions

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