Salesforce Developers with AI-Assisted Coding Experience
Remote · Americas
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Estimated pay
Estimate$99K–$197K/yr
Estimate — the employer hasn't published pay.
Based on 13 similar mid-level Software Engineering jobs among remote jobs worldwide that show pay. The range is the middle half of their posted pay (25th to 75th percentile), not an offer — ask the employer for the real range.
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At a glance
- Experience asked
- 6+ years
Skills mentioned
About the role
Headquarters:
We are looking for Salesforce Developers for a global company. Their goal is to accelerate Salesforce delivery across Flows, Lightning Web Components, and Apex while using AI copilots and agents to improve delivery speed, testing, and documentation.
General Information
- Location: Remote. Talents from the USA or Canada.
- Overlap: 6hs with East Coast time zone, USA
- Commitment: full-time
- Length: 12+ months
Required Skills:
- 3–6+ years of Salesforce development experience
- Strong hands-on experience with Apex
- Strong experience building Lightning Web Components (LWC)
- Strong experience with Salesforce Flow
- Experience with Git-based development and pull request workflows
- Strong automated testing mindset, including unit testing and security checks
- Experience validating Salesforce security, sharing rules, bulkification, and governor limits
- Experience integrating Salesforce components with APIs and MuleSoft-facing solutions
- Daily experience using AI copilots or coding agents for discovery, development, testing, and documentation
- Ability to review and validate AI-generated code before production deployment
- Experience participating in peer reviews, defect resolution, and production support
- Optional Skills (not mandatory):
- Experience with Salesforce Experience Cloud
- Experience with Salesforce Service Cloud
Deliverables
- Deliver Salesforce stories from a discovery-ready backlog through production, including tests and release notes
- Build and maintain Flows, Lightning Web Components, and Apex functionality on a bi-weekly delivery cadence
- Own pull requests, automated tests, defect fixes, and production-quality validation
- Build API and MuleSoft-facing components in close collaboration with integration engineers
- Use AI pair-programming for Flow, LWC, Apex, and unit-test scaffolding while independently validating production readiness
- Add automated tests and security checks within the same pull request as the related development work
- Validate bulkification, sharing, security, and Salesforce governor-limit compliance
- Participate in peer reviews and the P1 on-call rotation
- Contribute reusable AI prompts and development patterns that improve engineering quality and delivery efficiency
- Maintain accountability for production decisions and prevent untested AI-generated code from reaching production
- Engagement Highlights
- Full-time and long-term engagement with an Enterprise account at Toptal.
- Use AI copilots and coding agents as part of the daily engineering workflow.