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JAMS Platform Engineer
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Role : JAMS Platform Engineer.
Location: Toronto, ON
Hybrid (2-3 Days WFO)
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 ResponsibilitiesEngineer 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
Move JAMS from scheduler administration/operational role toward an engineered| observable and increasingly automated platformreducing manual intervention while improving resilience and recovery.
- Seniority Level
- Mid-Senior level
- Employment Type
- Contrac
More about this job
Responsibilities
Engineer and administer the JAMS workload automation platform, improving its reliability, performance, resilience, observability, and recovery through monitoring, troubleshooting, and automation. Modernize batch orchestration, support platform upgrades and production readiness, collaborate with application and infrastructure teams and the vendor, and apply practical AI capabilities to operational engineering.
Requirements
The role requires hands-on JAMS Scheduler experience, along with Python and PowerShell scripting, GitHub and CI/CD practices, REST APIs, SQL Server, and Windows Server troubleshooting. Candidates should have experience with monitoring and performance engineering; cloud exposure and practical familiarity with AI or generative AI tools are preferred.
Skills
- JAMS Scheduler
- Workload Automation
- Python
- PowerShell
- GitHub
- CI/CD
- REST APIs
- SQL Server
- Windows Server
- Monitoring and Observability
- Performance Engineering
- Distributed Systems Troubleshooting
- Cloud Technologies
- AI and Generative AI
- Event-Driven Scheduling
- Disaster Recovery
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
Keywords
- JAMS Scheduler
- Workload Automation
- Scheduler Administration
- Agents
- Executors
- Queues
- Resources
- Python
- PowerShell
- GitHub
- Git
- CI/CD
- REST APIs
- SQL Server
- Windows Server
- Monitoring
- Telemetry
- Performance Engineering
- Event-Driven Scheduling
- Batch Orchestration
- Automated Recovery
- Root-Cause Analysis
- Disaster Recovery
- Regression Testing
- AWS
- Cloud Technologies
- Artificial Intelligence
- Generative AI
- Anomaly Detection
- Production Readiness