Staff Backend SWE - Billing Platform

Location: Remote

Department: External Positions

Location Type: REMOTE

Employment Type: FULL_TIME

• Designing and building the backend services that power a new AI-native billing platform, hosted on GKE and built cloud-native from the ground up
• Integrating LLMs, ML models, and external AI services into billing workflows — with proper observability, fallback behaviour, and human review where appropriate
• Identifying and implementing practical AI opportunities across the SDLC: summarization, extraction, classification, recommendation, and workflow automation
• Partnering closely with a principal frontend engineer and cross-functional teams (product, design, data, operations) to turn complex billing pain points into scalable solutions
• Leading code reviews, establishing engineering best practices, and mentoring junior and mid-level engineers
• Contributing to technical direction and architecture decisions for a platform with a real end-of-year launch target

• 8+ years of professional software engineering experience
• Strong, production-depth Java and Spring Boot — this is their core backend language and a hard requirement
• RESTful APIs and microservices architecture at scale
• Hands-on React and frontend fluency — you're comfortable owning frontend work, not just aware of it
• Cloud platform experience: GCP preferred, AWS or Azure also fine; you understand cloud-native architecture in practice
• Containers, Kubernetes, CI/CD pipelines (Jenkins, Harness, Docker) — not just awareness, actual production use
• Database depth across relational and NoSQL: MySQL, PostgreSQL, MongoDB, DynamoDB
• You use AI tools every day across your full workflow — research, debugging, code generation, deployment. This isn't a nice-to-have; it's how they work and how they expect this person to work

• Recent TypeScript or Node.js experience alongside your Java background — they're evolving ther stack and that combination is genuinely valuable there
• Prior exposure to US healthcare billing, claims processing, or RCM — the domain has a steep learning curve and prior knowledge meaningfully accelerates impact
• Experience building production AI-enabled services — agentic workflows, LLM integration, evaluation frameworks, not just using Copilot
• Track record of greenfield platform delivery with real deadlines and real stakes