ScienceLogic SL1 Platform & Automation Specialist

Position Overview

The company is seeking an experienced ScienceLogic SL1 Platform & Automation Specialist to own, enhance, and extend our enterprise observability platform. The primary requirement for this role is deep, hands-on expertise with ScienceLogic SL1, including platform administration, reporting, customization, PowerPack development, and integration with AI-enabled and third-party systems.

The successful candidate will serve as the technical owner for SL1 and will translate operational, customer, and business requirements into reliable monitoring services, dashboards, reports, automations, and integrations. The role will work closely with Systems, Security, Network Operations, Service Delivery, Software Development, and business stakeholders to improve visibility, reduce manual effort, and turn monitoring data into actionable operational intelligence.

This position is ideal for an SL1 specialist who combines strong platform engineering skills with an integration and automation mindset, and who can help the company expand the value of SL1 through APIs, data services, AI-assisted operations, and connected enterprise platforms.

Employment Details

• Job Type: Full-Time

• Schedule: 8-hour shift; Monday through Friday; participation in an on-call rotation; availability for after-hours maintenance, upgrades, and incident response activities; occasional weekend work to support maintenance windows or critical incidents.

• Work Location: Remote

Key Responsibilities

ScienceLogic SL1 Platform Ownership

• Own the day-to-day administration, health, availability, performance, capacity, and lifecycle of the ScienceLogic SL1 platform stack.

• Manage SL1 platform components, collectors, credentials, device classes, discovery, organizations, access controls, and platform configuration.

• Plan and coordinate upgrades, patches, PowerPack updates, testing, release validation, and rollback readiness.

• Troubleshoot complex platform, collection, event, performance, and data-quality issues and coordinate remediation with internal teams and ScienceLogic support.

• Maintain platform standards, configuration control, technical debt registers, support procedures, and operational runbooks.

SL1 Customization & PowerPack Engineering

• Design, build, test, document, and maintain custom PowerPacks and associated SL1 content.

• Develop and maintain Dynamic Applications, event policies, device templates, dashboards, widgets, reports, Run Book Actions, Run Book Policies, ticket templates, credentials, and business service policies.

• Customize monitoring for network, cloud, infrastructure, application, telecom, and customer-facing services where standard content does not meet requirements.

• Use SL1 APIs, GraphQL/GQL capabilities, scripting, and supported development frameworks to extend platform functionality.

• Apply disciplined source control, peer review, test, release, and documentation practices to custom SL1 content.

Reporting, Dashboards & Service Visibility

• Create operational, executive, customer, SLA, availability, capacity, risk, and service-health reporting from SL1 data.

• Design role-appropriate dashboards that provide clear visibility into service health, infrastructure dependencies, events, trends, and business impact.

• Improve reporting accuracy, consistency, performance, scheduling, distribution, and data governance.

• Integrate SL1 data with reporting and analytics platforms, including Domo, Power BI, data services, and other approved enterprise tools.

• Partner with stakeholders to define meaningful metrics, thresholds, service models, and reporting outcomes.

Integrations, Automation & Third-Party Platforms

• Design, build, and support secure integrations between ScienceLogic SL1 and ITSM, ticketing, collaboration, analytics, security, cloud, network, and business platforms.

• Develop API-driven workflows using Python, PowerShell, REST APIs, webhooks, GraphQL/GQL, Logic Apps, Power Automate, or comparable technologies.

• Automate event enrichment, ticket creation and synchronization, notification, escalation, remediation, evidence collection, and reporting workflows.

• Manage integration credentials, service accounts, certificates, secrets, error handling, logging, monitoring, and recovery processes.

• Assess integration quality and remove brittle, duplicate, or manual workflows while maintaining appropriate change control.

AI-Assisted Operations & Innovation

• Identify and implement practical uses of AI to improve SL1 event analysis, alert summarization, incident enrichment, root-cause investigation, knowledge retrieval, reporting, and operator productivity.

• Expose approved SL1 data and capabilities to AI-enabled platforms through secure APIs, data pipelines, retrieval patterns, orchestration services, or governed agent integrations.

• Prototype and evaluate AI-assisted workflows while maintaining human oversight, data protection, access control, auditability, and operational safety.

• Partner with Security, IT, Development, and business stakeholders to define appropriate AI use cases and measurable outcomes.

• Document AI integrations, data flows, controls, limitations, support requirements, and fallback procedures.

Operational Excellence, Governance & Collaboration

• Act as the subject-matter expert and technical escalation point for ScienceLogic SL1.

• Collaborate with Network Operations, Systems, Security, Service Delivery, Software Development, vendors, and customers to translate requirements into maintainable platform capabilities.

• Maintain accurate architecture, configuration, data-flow, integration, support, and recovery documentation.

• Support incident, problem, change, vulnerability, and risk-management processes associated with the platform and its integrations.

• Provide knowledge transfer, mentoring, and practical guidance to teams that consume or support SL1 services.

• Promote secure engineering, least privilege, resilient design, and compliance with the company governance requirements.

Required Technical Skills

Expert Level

• ScienceLogic SL1 platform administration and architecture

• SL1 reporting, dashboards, widgets, service visibility, and operational analytics

• PowerPack development and lifecycle management

• Dynamic Applications and custom data collection

• Event policies, automation policies, Run Book Actions, and Run Book Automation

• SL1 platform troubleshooting, upgrades, collectors, performance, and data quality

• SL1 API integration and programmatic platform extension

Advanced Level

• Python and/or PowerShell development

• REST APIs, JSON, webhooks, authentication, and integration design

• GraphQL/GQL and data-query patterns relevant to SL1 integrations

• Monitoring, observability, event management, alert correlation, and service health

• Operational reporting and data visualization

• ITSM/ticketing platform integrations and workflow automation

• Secure credential, certificate, secret, and service-account management

• Technical documentation, testing, release management, and change control

Working Knowledge

• AI-assisted IT operations, retrieval-augmented generation, and agent-based workflows

• Microsoft Copilot, Copilot Studio, Azure AI services, or comparable enterprise AI platforms

• Logic Apps, Power Automate, Azure Automation, or comparable orchestration tools

• Domo, Power BI, data warehouses, or analytics platforms

• Cloud, virtualization, network, Linux, Windows, container, application, and telecom monitoring concepts

• ITIL-aligned incident, problem, and change management

• Security, privacy, auditability, and responsible AI governance principles

Required Experience & Qualifications

• Demonstrable, hands-on experience administering and customizing ScienceLogic SL1 in a production enterprise or service-provider environment.

• Proven delivery of custom SL1 reporting, dashboards, monitoring content, PowerPacks, or integrations.

• Experience building and supporting integrations between SL1 and third-party systems.

• Ability to diagnose complex monitoring, collection, event, performance, reporting, and data-quality issues.

• Strong written and verbal communication with the ability to translate operational needs into technical solutions.

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.

Preferred Skills & Experience

• Experience operating ScienceLogic SL1 in an MSP, telecommunications, network-services, or multi-customer environment.

• Experience developing custom PowerPacks using supported SL1 development methods, APIs, scripting, and GraphQL/GQL.

• Experience integrating SL1 with ITSM platforms such as Autotask PSA, ServiceNow, or comparable systems.

• Experience delivering customer-facing SLA, availability, capacity, service-health, and executive reporting.

• Experience integrating SL1 data with Domo, Power BI, data lakes, or other analytics platforms.

• Experience applying AI to event summarization, alert enrichment, root-cause assistance, knowledge retrieval, workflow orchestration, or operational reporting.

• Experience with network, cloud, infrastructure, application, container, and service-level observability.

• Experience supporting globally distributed or remote-first technical teams.

• Experience maintaining audit-ready platform documentation and controlled release processes.

Preferred Certifications

ScienceLogic - Highest Priority

• Current or recent ScienceLogic SL1 certification appropriate to platform administration, engineering, or development

• ScienceLogic Certified Expert or comparable advanced ScienceLogic accreditation

Additional

• ITIL Foundation or higher

• Microsoft Azure, Power Platform, AI, data, or automation certifications

• Relevant Python, API, observability, cloud, or service-management certifications

Candidate Evidence We Would Value

• Examples of custom PowerPacks, Dynamic Applications, reports, dashboards, or integrations the candidate personally designed or maintained.

• A clear explanation of an SL1 API integration, including authentication, data flow, error handling, monitoring, and support model.

• Examples of improving SL1 data quality, event fidelity, reporting usefulness, platform performance, or supportability.

• A practical approach for using AI with SL1 while protecting sensitive data and retaining human oversight.

• Technical documentation or architecture examples that show disciplined engineering and operational ownership.

Success Measures

• SL1 availability, collection health, data quality, and platform reliability targets are achieved.

• Custom monitoring and reporting requirements are delivered accurately, securely, and maintainably.

• PowerPacks and custom SL1 content follow documented development, testing, release, and lifecycle standards.

• Operational, executive, customer, and SLA reporting becomes more reliable, useful, and timely.

• Integration failures, manual handoffs, duplicate effort, and unsupported customizations are reduced.

• Monitoring coverage and event quality improve while avoidable alert noise is reduced.

• AI-assisted use cases produce measurable operational value without weakening security, privacy, governance, or human oversight.

• Platform upgrades, lifecycle activities, and vendor escalations are planned and executed effectively.

• Teams receive high-quality documentation, knowledge transfer, and dependable technical escalation support.

• ScienceLogic SL1 data is used more effectively to drive operational decisions, customer outcomes, and continuous improvement.

Role Profile

• Primary specialty: ScienceLogic SL1 platform engineering, reporting, customization, and integration.

• Secondary specialty: Automation, APIs, analytics, and AI-assisted operations.

• Operating style: Hands-on technical ownership with strong stakeholder communication and documentation discipline.

• Business outcome: A reliable, extensible, and well-governed observability platform that converts monitoring data into actionable intelligence.