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Salary: USD 160,000 - 200,000 / annual
Temporal is an open-source programming model that simplifies code, improves application reliability, and helps developers ship faster. As a Senior Professional Services Engineer, you will partner directly with customers and partners to move from design to production-ready Temporal implementations quickly and safely.
You will deliver production-ready systems by co-building initial workflows with customer engineering teams, implementing and teaching production-safe patterns including retries, timeouts, heartbeats, determinism, and versioning. You'll help customers stand up and operate Temporal Server in production across cloud and self-hosted environments, defining worker deployment, scaling, and operational guardrails including upgrade strategy, failure handling, and capacity planning.
Key responsibilities include establishing observability and reliability standards by defining metrics, alerts, and dashboards; creating repeatable runbooks, templates, examples, and documentation that improve delivery quality; leading hands-on workshops and training to enable customer engineers to operate independently; and owning complex technical delivery issues end-to-end, partnering with Support and Platform Architects to reduce escalations.
You will bring experience delivering and operating production systems where reliability and incident response matter, with strong understanding of distributed systems, failure modes, scaling tradeoffs, and operational safety. You need hands-on coding ability in Go, Java, Python, or TypeScript; experience deploying and operating production services in cloud and self-hosted environments; and ability to design and communicate operational standards including on-call readiness, runbooks, and capacity planning.
You should be comfortable working directly with customers in high-stakes delivery moments with a calm and credible approach, possess strong debugging skills, navigate ambiguity and real-world constraints, and have the ability to teach and enable other engineers rather than just delivering work directly. Nice-to-haves include experience with workflow orchestration systems, building observability programs, creating reusable reference architectures, and background in services delivery models at scale.
