ServiceNow Discovery Engineer ID80139
On-siteKoseze, Vodice, Republic of Slovenia
Job Summary
Design and build AI agents that continuously analyze ServiceNow Discovery logs, execution results, and errors at scale to classify failures, identify root causes, and recommend corrective actions. Develop capabilities for agents to generate corrections to Discovery probes and patterns with appropriate testing guardrails and human approval. Build agents that assess MID Server health, throughput, and coverage while collecting and interpreting metrics from monitoring platforms. Convert operational knowledge and runbooks into reusable agentic workflows to improve Discovery reliability. Requires 4+ years of hands-on ServiceNow Discovery experience, including MID Servers, Patterns/Probes, and CMDB/CSDM data quality, plus proficiency with Prometheus, OpenTelemetry, and Grafana. This role sits within an enterprise-scale squad executing discovery across millions of infrastructure targets on daily and weekly schedules.
Required Qualifications
- Hands-on experience with ServiceNow Discovery of at least 4 years, including MID Servers, Discovery Patterns/Probes, credentials, schedules, Discovery Status, ECC Queue, and troubleshooting Discovery failures
- Experience developing or modifying ServiceNow Discovery Patterns and Probes and understanding how infrastructure attributes and relationships are discovered
- Experience with ServiceNow CMDB/CSDM, Configuration Items (CIs), identification/reconciliation, relationships, and CMDB data quality
- Upper-intermediate English level
Desired Qualifications
- Advanced Python development experience and REST API design capabilities with experience building APIs, data-processing pipelines, integrations, automation, and production-grade engineering solutions
- Strong experience with modern software development and SDLC practices and toolchains, including Git/GitHub, Jenkins or equivalent CI/CD platforms, artifact repositories, automated testing, code quality/security scanning, release management, and deployment automation
- Practical experience integrating Gen AI APIs into software applications (e.g., OpenAI, Anthropic) and a working understanding of developer-level concepts like Retrieval-Augmented Generation (RAG) and Vector databases
- Practical knowledge of Infrastructure Engineering with Linux, Windows Server, compute, virtualization/cloud infrastructure, authentication, processes/services, and infrastructure troubleshooting
- Working knowledge of TCP/IP, DNS, routing, firewalls, ports, SSH, WMI/WinRM, SNMP, HTTP/S, and common network and infrastructure troubleshooting techniques
- Experience with high-volume logs, metrics, errors, and operational datasets to identify patterns, anomalies, trends, and root causes and turn them into actionable engineering improvements
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