This role pays less than
75%
of similar roles. Most pay
$155,000–$207,350
— the shaded band above.
At the midpoint, this role pays about
$152k
versus about
$181k
for comparable roles.
Based on 238 similar postings.
Employer
About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has
1103 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 985 roles with salary data.
As a Service Engineer at Azure EngOps’ Customer Reliability Engineering team, you will design and build AI-powered solutions that prevent operational issues before they impact customers. Your day-to-day involves creating intelligent agents, LLM-driven workflows, and automation tools to streamline incident triage and customer impact assessment. You’ll also develop data pipelines integrating systems like Azure DevOps and Data Explorer, automating manual processes and building self-healing capabilities. Collaborating with cross-functional teams, you will translate business needs into technical solutions, participate in design reviews, and ensure operational excellence through metrics-driven assessments. This role requires proficiency in AI/ML technologies, big data concepts, and experience with platforms like Azure Data Explorer and Kusto/KQL for query writing and visualization. Ideal candidates bring a strong engineering mindset, cross-team collaboration skills, and the ability to adapt quickly in unpredictable cloud operations environments.
Build intelligent agents and LLM-powered workflows to automate incident triage and customer impact assessment.
Maintain data integrations across systems like Azure DevOps, Data Explorer, and other platforms to reduce manual processes.
Translate business requirements into technical solutions by collaborating with cross-functional teams on design reviews.
Adapt quickly to unpredictable cloud operations, prioritizing tasks during incidents and engaging in major cloud issues when needed.
Use metrics to evaluate operational effectiveness, platform health, and the impact of reliability improvements.
What we're looking for
2+ years of technical experience in software engineering, network engineering, service engineering, systems engineering, or industrial controls
Bachelor's degree in Computer Science, Information Technology, Mechanical/Electrical/Aerospace Engineering, Data Science, Cybersecurity, or related field
Experience with AI/ML technologies including large language models (LLMs) and agentic frameworks
Familiarity with operational data platforms like Azure Data Explorer, Azure DevOps APIs, and monitoring systems
Proficiency in big data concepts, Kusto/KQL query writing, and statistical software such as Python or R
Strong problem-solving skills and ability to work effectively under pressure in high-stakes scenarios