Sr. AI Engineer - IT

LogicMonitor is hiring a hands-on Senior AI Engineer to implement, improve, and support components of its enterprise AI operating layer. The role builds and operates AI agent services, skills management, integrations, permission-aware context assembly, model routing, and operational controls.

Responsibilities:

• Implement and support assigned services in our enterprise AI operating layer for agent execution, context assembly, model routing, tool access, workflow orchestration, and enterprise integrations
• Implement the approved skills-store model: core skills available to everyone, personal skills, team or department skills, and organization-wide skills. Help the shared main agent select skills appropriate to each user and task
• Build self-service features that let users create, test, manage, and use personal skills. Implement the approved review and promotion process for team, department, and organization-wide skills
• Implement skill versioning, selection, testing, auditability, and permission checks. Surface conflicts or policy gaps with options and evidence for the AI Fabric lead and relevant approvers
• Build and use agent harnesses under agreed runtime patterns, including configuration, skill and tool loading, execution controls, tracing, tests, and failure handling
• Develop agents and services in code, using workflow tools where they fit. Integrate APIs, data platforms, tools, and external agents while handling authentication, retries, rate limits, duplicate requests, and recovery
• Apply approved identity and authorization patterns. Implement permission-aware context assembly using approved source-authority, freshness, citation, and context-window rules. Implement approved model routing based on task, policy, quality, latency, and cost, with tests and telemetry for routing decisions
• Add evaluations, logging, alerts, runbooks, and usage and cost measures to the components you build and support
• Implement and document components using the platform’s established interfaces and patterns. Recommend improvements; the AI Fabric lead decides which changes become shared standards
• Contribute to bounded pilots for background agents as the operating layer matures, using approved task limits, authorization, monitoring, review points, and outcome checks