Senior Observability AIOps engineer

A hands-on senior engineer who bridges traditional observability, APM, and ITSM practices with modern AIOps and AI-driven operations, using Python-based automation and AI/LLM tooling to improve incident response and operational efficiency.

Key Responsibilities and Duties

• Engineering and integrating monitoring and observability platforms with enterprise systems

• Troubleshooting complex application and infrastructure issues

• Developing Python-based automation and API integrations • Applying ITSM principles to monitoring, event, incident, problem, and change management

• Using AIOps capabilities to reduce alert noise and accelerate root-cause analysis

• Creating effective technical documentation and knowledge bases

• Working effectively with engineering, application, infrastructure, architecture, and operations teams

Educational Requirements

• Bachelor's Degree Preferred

Work Experience

• 3+ Years Required; 5+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level
7IC

Required Skills:

• 3+ years of hands-on experience with Splunk (SPL, dashboards, alerts, data onboarding) as an Administrator, Power User, or Developer
• 3+ years of experience of IT Service Management practices — Incident, Problem, Change, Event, and Service Request Management tool using ServiceNow.
• 3+ years of experience administering a market-leading APM/observability platform (e.g., Splunk Cloud Observability/SignalFX, Dynatrace, Sysdig, Datadog), with solid understanding of metrics, logs, traces, and SLI/SLO/SLA concepts
• 3+ years of hands-on Python development skills for scripting, automation, API integration, and data processing; ability to write production-quality code independently
• Working knowledge of LLMs, Generative AI, AI agents, and AI-assisted troubleshooting/automation (e.g., RAG, prompt engineering, agentic AI concepts).
• Comfortable navigating and troubleshooting across both Linux and Windows environments in production/enterprise settings.

Preferred Skills:

• Experience with AIOps capabilities such as event correlation, noise reduction, and automated root-cause analysis
• Familiarity with MCP (Model Context Protocol) for connecting AI agents to enterprise data/tools
• Exposure to AI IDE tools (e.g., Kiro, Amazon Q) or LLM APIs (OpenAI, Anthropic, Google)
• Experience with incident/event management tools like PagerDuty or Moogsoft
• Familiarity with Jira for issue tracking, workflow management, or agile project coordination
• Knowledge of REST API development, JSON, and API integration patterns
• Cloud platform experience (AWS, Azure, or GCP)

Anticipated Posting End Date:

Actual base salary may vary based upon, but not limited to, relevant experience, time in role, base salary of internal peers, prior performance, business sector, and geographic location. In addition to base salary, the competitive compensation package may include, depending on the role, participation in an incentive program linked to performance (for example, annual discretionary incentive programs, non-annual sales incentive plans, or other non-annual incentive plans). 

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