Observability Engineer

OpenLoop Health•Des Moines, IA

About The Position

OpenLoop is hiring an Observability Engineer to build its observability practice from scratch. The role will establish how enterprise systems are monitored, how alerts are designed, and how uptime and reliability are measured. The engineer will instrument SaaS and internal tools in Datadog, manage alerting and escalation in PagerDuty, and create visibility for systems with limited native observability by retrieving logs, using APIs, or building lightweight integrations and tools. The role also monitors end-to-end business workflows across systems and partners with IT Service Management on incident response, root-cause analysis, and change validation. The engineer will use scripting and AI-assisted development to build quickly and continually improve signal quality.

Requirements

3+ years of experience building observability functions, including dashboards, monitors, and alerting.
Hands-on experience with Datadog.
Hands-on experience with PagerDuty.
Scripting and API experience, such as Python, to retrieve logs and data from systems without native integrations.
A track record of building observability or monitoring capabilities where little existed before.

Nice To Haves

Startup or high-growth company experience.
Experience monitoring SaaS business applications, not only infrastructure.
Experience with OpenTelemetry or other log and metrics pipelines.
Experience with ITSM tools and incident or change management, such as Jira Service Management.
Experience using AI-assisted development to build internal tools.

Responsibilities

Define what to monitor, how to alert, and how to measure uptime and reliability across enterprise systems.
Build Datadog dashboards and monitors for availability, capacity, performance, and concurrency limits across SaaS and internal tools.
Design PagerDuty alert routing and escalation so the appropriate people are notified quickly and with minimal noise.
Create visibility for systems with little or no native observability by pulling logs, using APIs, or building lightweight integrations and tools.
Monitor critical end-to-end workflows across multiple systems to identify and address process failures.
Partner with IT Service Management on incident response, root-cause analysis, and change validation.
Use scripting and AI-assisted development to build tools and improve signal quality as the observability practice matures.