Backend Java Engineer - Revenue Cloud Rating
leadout capitalMillbrae (CA)
Backend Java Engineer - Revenue Cloud Rating
Posted 2 days ago
leadout capitalMillbrae (CA)
SENIORITY
Lead
About the role
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 DoingDesign, 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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