temporal - Software Engineer II, Cloud Applications
Requirements
• Experience building and operating production backend systems in a cloud environment. • Proficiency in Go or another applicable backend or systems language, with the ability to ramp up in an existing codebase. • Strong computer science fundamentals, including data structures, concurrency basics, testing, and debugging. • Working knowledge of distributed-systems concepts such as reliability, fault tolerance, consistency, scaling, and failure handling. • Experience with databases, data pipelines, messaging systems, or object storage. • The ability to take a scoped problem, break it into smaller tasks, implement a solution end to end, and incorporate feedback. • An operational mindset, including familiarity with logging, metrics, tracing, deployment, and production troubleshooting. • Comfort collaborating across teams and communicating progress, risks, and technical tradeoffs clearly. • A commitment to correctness, maintainability, and leaving systems better than you found them. • Experience with PostgreSQL, Redshift, Kinesis, Firehose • Experience with S3, Google Cloud Storage, Azure Blob Storage, or other object-storage systems. • Familiarity with Kubernetes and cloud infrastructure. • Experience supporting on-call rotations, investigating incidents, or improving production observability. • Familiarity with Temporal concepts—or a strong interest in learning the platform. • TECHNOLOGY STACK • Primary language: Go • Data storage: PostgreSQL, Redshift, S3,Google Cloud Storage, Azure Blob Storage, ClickHouse • Data processing: Kinesis, Firehose • Infrastructure: Kubernetes • Core framework: Temporal • You do not need experience with every technology in our stack. We value strong engineering fundamentals and the ability to learn unfamiliar systems.
Responsibilities
• Design, implement, test, and ship well-scoped features and improvements for Temporal Cloud with support from teammates. • Build and improve services that support namespace provisioning, configuration, scalability, and reliability. • Develop data pipelines that process high-volume usage and operational data across multiple tenants. • Make thoughtful engineering tradeoffs with guidance, balancing data freshness, query cost, tenant isolation, reliability, and operational complexity. • Improve service operability through tests, instrumentation, dashboards, alerts, runbooks, and documentation. • Participate in code reviews, design discussions, incident response, and production debugging. • Collaborate across engineering, product, and customer-facing teams to understand requirements and deliver scoped projects safely. • Improve developer and customer experience through automation, better tooling, and incremental product improvements.
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