Staff Software Engineer - Orders Platform

Accountabilities: Act as a technical architect within the Orders Platform team, defining and evolving how order data is modeled, stored, replicated, synchronized, and reconciled. Design, build, and maintain event-sourced and replicated-state systems that remain reliable under retries, network partitions, concurrent updates, and partial failures. Strengthen the platform's offline-first architecture, ensuring restaurant ordering and point-of-sale workflows continue operating reliably even when connectivity is interrupted. Develop robust mechanisms for idempotency, optimistic concurrency, event replay, projections, conflict resolution, and data reconciliation. Partner closely with Product, Payments, Reporting, and engineering teams responsible for point-of-sale and mobile experiences to deliver reliable ordering flows end to end. Lead technical design discussions, review architecture and code, and establish engineering standards that improve system correctness, scalability, and maintainability. Mentor and support engineers, helping the team develop deeper expertise in distributed systems and the platform's core architectural patterns. Improve observability, replay, and recovery capabilities so that order-state issues can be identified, investigated, and resolved quickly and cost-effectively. Reduce dependency on individual team members by documenting architectural decisions, sharing technical context, and making complex platform behavior easier to understand. Build familiarity with specialized technologies and continuously improve their reliability as the platform and engineering organization scale. Maintain a customer-focused approach by understanding restaurant operators' needs and, when necessary, engaging directly with customers through visits, calls, or other communication channels. Requirements: Extensive experience building and operating correctness-critical distributed systems. Hands-on experience with event sourcing, CRDTs, or comparable approaches to replicated and offline-first data management, such as synchronization engines or conflict-resolution layers. Strong understanding of idempotency, optimistic concurrency, event replay, projections, reconciliation, and distributed data consistency. Ability to reason through complex failure scenarios, including interrupted operations, unavailable nodes, network partitions, and concurrent changes. Staff-level engineering experience, with a proven ability to influence technical direction, lead architectural decisions, and remain actively involved in hands-on development. Strong backend engineering skills and the ability to quickly learn specialized technologies and make complex systems more resilient. Clear written and verbal communication skills, with the ability to explain sophisticated technical concepts and make system knowledge accessible to others. Experience mentoring engineers, reviewing technical designs, and helping teams adopt sound engineering practices. Preferred: Backend engineering experience in payment processing or ordering systems. Preferred: Ability to collaborate with payments and reporting teams while owning the order-related components of financial transaction workflows. A strong customer-oriented mindset and willingness to engage directly with restaurant operators to understand and solve operational challenges. Experience in restaurants, retail, or IT environments is considered an advantage but is not required. Familiarity with technologies in the platform's ecosystem is beneficial, including Kotlin, TypeScript, React, React Native, Kubernetes, ArgoCD, Datadog, PostgreSQL, SQLite, OpenTelemetry Collectors, and Kafka. Benefits: Estimated starting base salary of $240,000–$260,000 USD, depending on level, location, and experience. Generous pre-IPO equity package. Comprehensive health coverage. Remote-first work environment with the flexibility to work from anywhere. Unlimited paid time off (PTO). Additional employee perks and benefits. Opportunity to influence the architecture of a business-critical platform and work on complex distributed systems at scale.