Salesforce Developer

Salesforce Salesforce · Enterprise · Dublin, Ireland

This role is for a Hybrid Senior Developer at Salesforce, focusing on the full development lifecycle of AI-driven features within the Salesforce platform. The role involves 70% feature development (Apex, MuleSoft) and 30% automation engineering, including designing and maintaining E2E testing scripts. A key aspect is integrating AI agents into human workflows, contributing to shared system context for AI reliability, and critically evaluating AI-generated code. The position requires experience with Salesforce development, MuleSoft, QA automation, CI/CD, and a strong emphasis on using AI tools in development workflows, including prompt engineering.

What you'd actually do

  1. Hybrid Delivery: Own the full development lifecycle. Balance your time between 70% feature development (Salesforce/MuleSoft) and 30% automation frameworks and quality gates.
  2. Automation Engineering: Design and maintain automated E2E testing scripts using tools like Selenium, Provar, or Playwright to validate complex Salesforce workflows.
  3. Quality Advocacy: Lead code and test-plan reviews. Ensure every line of code is backed by meaningful unit tests (Apex) and integration tests (MuleSoft/MUnit).
  4. Integration Support: Develop integration flows in MuleSoft and ensure resilience through automated interface and contract testing.
  5. Shift-Left Strategy: Partner with Product Owners to define "Definition of Done" and "Acceptance Criteria," baking quality into the requirement stage.

Skills

Required

  • Salesforce Dev: 4+ years of hands-on experience with LWC, Apex, and Flows.
  • MuleSoft: Basic experience with Anypoint Platform, building flows, and testing API responses.
  • QA Automation: Proven experience building frameworks for Salesforce (Apex Unit Testing, MUnit, Browser Automation).
  • DevOps: Strong grasp of CI/CD pipelines and integrating automated tests into the deployment process.
  • AI Innovation: Familiarity with Salesforce Agentforce and automating the testing of AI-driven interactions.
  • A demonstrated, genuine AI-first approach to engineering — using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
  • Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows.
  • Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.

What the JD emphasized

  • AI agents integrate seamlessly into human workflows
  • Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
  • Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.

Other signals

  • AI agents integrate seamlessly into human workflows
  • Critically evaluate code (human or AI-generated)
  • Advanced prompt engineering skills