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Backend Java Engineer - Revenue Cloud Rating

Salesforce
Remote, GBR
Full-time
Mid · 4–5 years experience
Remote
Discovered 1 weeks ago

Full Job Posting

The Experience

Revenue Cloud Rating is a newly formed engineering team inside Salesforce's Revenue Cloud organization, created through our acquisition of m3ter, and we're rebuilding our event-driven microservices platform on Salesforce's own infrastructure to rate complex, usage-based pricing at high volume and low latency.

As a Member of Technical Staff, you'll join a fully remote, UK-based team to help carry both the product and the team through this transition, with Agentforce increasingly part of how we design and build.

What You'Ll Actually Be Doing

  • Design, build, and operate backend services within our Java-based, event-driven microservices architecture, with AI as a core part of your development workflow to deliver secure, optimized, high-quality code.
  • Make sound technical decisions with incomplete information as the team learns and builds in parallel.
  • Critically evaluate code — your own, your teammates', and AI-generated — for correctness, quality, security, and performance.

You're Our Person If...

  • You have 4-5 years of backend Java experience, including building and operating microservice and event-driven architectures.
  • You bring a strong tolerance for ambiguity, with the judgment to work independently and make decisions as a team and product transition into a new organization.
  • You have hands-on experience with AI development tools (e.g., GitHub Copilot, Cursor, Claude Code, Codex) as part of your regular workflow, with the prompt engineering skill to make outputs reliable and production-ready.
  • Experience will be evaluated based on alignment to the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer work, etc.).

Even Better If...

  • You've worked through a team or product integration following an acquisition.
  • You have experience working with high throughput, low latency systems, whilst applying complex business logic.
  • You've contributed to a shared system context — documented design standards and constraints that help AI tools operate reliably.

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