Senior DevOps Engineer, Salesforce Platform
Technology
Job Description
Job Title: Senior DevOps Engineer, Salesforce Platform
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Location: Chicago IL (4 days onsite per week)
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Term: Contract
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Experience: 7 to 10 years overall, 4+ years in Salesforce release engineering
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Role Summary: Own CI/CD pipeline architecture, sandbox strategy, and release governance for our Salesforce platform, while bringing AI assisted tooling into the delivery pipeline to speed up testing, code review, and deployment risk detection.
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Key Responsibilities
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- Design and maintain CI/CD pipelines for Salesforce metadata and code across sandboxes, UAT, and production
- Own sandbox strategy (scratch orgs, partial/full copy, refresh scheduling) and branching strategy for SFDX projects
- Implement automated test gates: Apex coverage thresholds, static analysis (PMD, Salesforce Code Analyzer), security scans
- Manage deployment tooling (Copado, Gearset, AutoRabit, Flosum, or native SFDX/CLI scripting)
- Build rollback procedures and production incident response for failed deployments
- Introduce AI assisted code review and test generation into the pipeline to catch risky Apex/LWC changes before merge
- Manage secrets and connected app auth (JWT bearer, OAuth) across the toolchain
- Monitor org limits, API usage, and platform health with proactive alerting
- Partner with Admins, Apex, and LWC developers to reduce manual deployment friction
- Mentor mid level engineers on DevOps practices specific to Salesforce
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Required Skills
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- Deep hands on SFDX, Salesforce CLI, metadata API deployments
- Production experience with Copado, Gearset, AutoRabit, or Flosum
- Strong Git (branching, PR gating, conflict resolution in metadata heavy repos)
- CI/CD platform build experience (Jenkins, GitHub Actions, GitLab CI, or Azure DevOps)
- Working knowledge of Apex and LWC, enough to troubleshoot deployment failures
- Scripting proficiency (Python, Bash, or Node.js)
- Understanding of governor limits and their effect on deployment/testing strategy
- AI Skills (basic, expected of any senior candidate today)
- Practical experience using AI coding assistants (GitHub Copilot, Claude Code, or similar) inside a real delivery workflow, not just casual use
- BMad is a big plus
- Basic understanding of where AI adds risk in a regulated deployment pipeline (hallucinated logic, data leakage through prompts) and how to guard against it
- Exposure to using an LLM for log analysis or root cause triage during deployment failures
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Preferred
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- Salesforce certifications: Platform Developer I/II, Administrator
- Experience with Salesforce DevOps Center
- Regulated industry experience
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