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SRE/ Platform Engineer

  • ON, Canada
  • Ontario, Canada, Canada

Contract

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Contract
Closing date
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

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

Move JAMS from scheduler administration/operational role toward an engineered| observable and increasingly automated platform reducing manual intervention while improving resilience and recovery.

More about this job

Responsibilities

Engineer and administer the JAMS workload automation platform, improving its reliability, performance, observability, and resilience through monitoring, troubleshooting, and automated recovery. Develop automation and engineering standards, modernize batch orchestration, support production readiness and disaster recovery, and collaborate with application, infrastructure, and vendor teams.

Requirements

The role requires hands-on experience with JAMS Scheduler and workload automation, along with Python or PowerShell, GitHub/Git, CI/CD, REST APIs, SQL Server, and Windows Server troubleshooting. It also calls for monitoring and performance engineering experience, with cloud and practical AI/GenAI exposure preferred.

Skills

  • JAMS Scheduler
  • Workload Automation
  • Python
  • PowerShell
  • GitHub
  • Git
  • CI/CD
  • REST APIs
  • SQL Server
  • Windows Server
  • Monitoring and Observability
  • Performance Engineering
  • AWS and Cloud Technologies
  • AI and Generative AI
  • Incident Troubleshooting
  • Disaster Recovery

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics

Keywords

  • JAMS Scheduler
  • Workload Automation
  • Scheduler Agents
  • Executors
  • Queues
  • Resources
  • Batch Workflows
  • Python
  • PowerShell
  • REST APIs
  • GitHub
  • Git
  • CI/CD
  • SQL Server
  • Windows Server
  • Monitoring
  • Telemetry
  • Performance Engineering
  • Root-Cause Analysis
  • Automated Recovery
  • Event-Driven Scheduling
  • Batch Orchestration
  • Regression Testing
  • Disaster Recovery
  • AWS
  • Cloud Technologies
  • AI
  • Generative AI
  • Anomaly Detection
  • Production Readiness

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