JAMS Platform Engineer

Toronto, ON
Hybrid
Posted Oct 3, 2026
1 position

$65–$70 / hour

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Employment type: Contract
Experience level: Lead · 10+ years
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Engineer and support the JAMS scheduling platform and workload automation, including troubleshooting Windows Server, distributed applications, and SQL Server databases. Apply scripting, systems integration, monitoring, and performance engineering practices, with exposure to cloud and AI tools.

Job details

Job Title: JAMS Platform Engineer Location: Toronto, ON Work Arrangement: Hybrid-2-3 days/ week Employment Type: Contract Pay Rate: CAD 65-70/Hour Domain: BFSI Application Deadline: Oct. 15th 2026 Skills: Should have 10+ years of exp. Strong hands-on experience with JAMS Scheduler and workload automation Proficiency in Python and PowerShell scripting Experience with GitHub/Git, CI/CD pipelines, and software engineering best practices Strong knowledge of REST APIs and systems integration Experience with SQL Server and database troubleshooting Hands-on experience troubleshooting Windows Server and distributed applications Experience with monitoring, telemetry, and performance engineering Exposure to AWS and cloud technologies preferred Practical understanding of AI/GenAI tools and willingness to apply AI to operational engineering EEOC Compliance: We are an equal opportunity employer, and all qualified applicants will receive consideration for employment. DISCLAIMER AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.

What you’ll do

Requirements

Requires 10+ years of experience and strong hands-on expertise with JAMS Scheduler and workload automation. Candidates should be proficient in Python and PowerShell, Git and CI/CD, REST APIs, SQL Server, and Windows Server troubleshooting; AWS and practical use of AI/GenAI tools are preferred.