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JAMS Platform Engineer

  • Toronto, ON, Canada

$60 to $68 CAD / hour · Contract

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Job details

Pay
$60 to $68 CAD / hour
Job type
Contract
Apply by
Experience
Minimum 10 years experience required
Posting language
English
Posted

Original job description

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

More about this job

Responsibilities

Engineer and administer the JAMS workload automation platform, improving its reliability, performance, resilience, observability, and recovery through monitoring and automation. Modernize scheduling and batch orchestration, support upgrades and production readiness, collaborate with application and infrastructure teams, and apply practical AI capabilities to operational engineering.

Requirements

Requires at least 10 years of experience and strong hands-on expertise with JAMS Scheduler and workload automation. Candidates should have experience with Python or PowerShell, GitHub and CI/CD, APIs, SQL Server, Windows Server, monitoring, and troubleshooting; cloud and practical AI experience are preferred.

Skills

  • JAMS Scheduler
  • Python
  • PowerShell
  • GitHub
  • Git
  • CI/CD
  • REST APIs
  • SQL Server
  • Windows Server
  • Workload Automation
  • Monitoring And Observability
  • Performance Engineering
  • Distributed Applications
  • Cloud Technologies
  • AI And Generative AI
  • Batch Orchestration

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
  • Observability
  • Performance Engineering
  • Automated Recovery
  • Event-Driven Scheduling
  • Batch Orchestration
  • Regression Testing
  • Disaster Recovery
  • Production Readiness
  • AWS
  • Cloud Technologies
  • AI
  • Generative AI
  • Anomaly Detection

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