ServiceNow Discovery Engineer ID80139
On-siteTernopil, Ternopil, Ukraine
Job Summary
Design and build AI agents that continuously analyze ServiceNow Discovery logs, classify failures, and identify root causes to generate corrections for probes and patterns. Develop capabilities to assess MID Server health, throughput, and coverage while converting operational knowledge into reusable agentic workflows. Build agents that collect and interpret metrics from logs, monitoring platforms, and telemetry sources to improve Discovery reliability. Requires 4+ years of hands-on ServiceNow Discovery experience, proficiency with Python and REST APIs, and knowledge of Prometheus, OpenTelemetry, and Grafana. Work 100% remotely with flexible hours within an Inc. 5000 company leading in application development and AI/ML.
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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