JAMS Platform Engineer
Toronto, ON - Hybrid (2-3 Days WFO)
6-12 months
Minimum 10 years experience required
Note- Move JAMS from scheduler administration/operational role toward an engineered| observable and increasingly automated platform reducing manual intervention while improving resilience and recovery.
Role Summary
Seeking a hands-on engineer to drive the reliability| automation and modernization of the enterprise JAMS workload automation platform.
The role combines JAMS platform expertise with software engineering| automation and AI capabilities.
Key Responsibilities
Engineer and administer JAMS Scheduler| including Scheduler| Agents| Executors| queues| resources and job configuration.
Improve platform reliability| performance| capacity| resilience and observability.
Lead complex troubleshooting| performance analysis and root-cause investigations.
Build proactive monitoring and automated recovery for Scheduler| agents| queues and batch workflows.
Develop automation using Python| PowerShell| APIs and scripting to reduce manual operational effort.
Build and maintain engineering solutions using GitHub| including source control| code review and CI/CD practices.
Drive migration from time-based to event-driven scheduling and simplify batch orchestration. Establish engineering standards for retries| long-running jobs| alerts| resources| agents and job design.
Support upgrades| patching| regression testing| DR and production readiness.
Partner with BatchOps| application and infrastructure teams to onboard and optimize workloads. Work with the JAMS vendor on product defects| performance and roadmap capabilities.
Explore and implement practical AI use cases for operational analytics| anomaly detection| troubleshooting and automation.
Technical Skills
Strong hands-on JAMS Scheduler / workload automation experience Python and PowerShell GitHub / Git| CI/CD and software engineering practices REST APIs and systems integration SQL Server and database troubleshooting Windows Server and distributed application troubleshooting Monitoring| telemetry and performance engineering Exposure to AWS/cloud technologies preferred Practical understanding of AI/GenAI tooling and willingness to apply AI to operational engineering Success in the Role
