Systems Development Engineer

Investigate and resolve customer-impacting production issues across cloud infrastructure, workflow execution, access control, storage, networking, deployment systems, and observability.

Identify patterns in customer issues and convert them into automation, product improvements, runbooks, tests, or design changes.

Build internal tools and diagnostics that make production issues easier to detect, understand, and resolve.

Improve platform observability, including logs, metrics, dashboards, alerts, and customer-visible debugging information.

Participate in design and development so systems are easier to operate, debug, and support, and guide engineering teams toward durable fixes.

Define and uphold operational engineering practices: production readiness, alert quality, runbook discipline, observability standards, regression prevention, and code quality.

Drive measurable reductions in on-call pages, recurring customer issues, manual operational work, and time-to-resolution.

Strong software engineering skills in Python, Go, Java, or a similar language.

Experience debugging production systems across multiple layers of the stack.

Practical knowledge of Kubernetes, Linux, cloud infrastructure, distributed systems, networking, storage, and IAM.

Experience with infrastructure-as-code, deployment systems, CI/CD, observability, and operational automation.

Ability to move from ambiguous customer symptoms to clear technical diagnosis and durable remediation.

Strong judgment about when to fix directly, automate, escalate, redesign, or build a broader platform improvement.

Clear written and verbal communication, especially around root cause analysis, technical recommendations, runbooks, and design feedback.

A bias toward reducing toil through engineering rather than repeatedly solving the same issue by hand.

Operating customer-facing SaaS, cloud infrastructure, self-hosted or on-prem deployments, or workflow orchestration systems.

Batch workloads, autoscaling, capacity management, identity and access systems, storage systems, or platform observability.

Improving on-call health, reducing ticket volume, or building production diagnostics.

Working across support, customer success, product, and engineering teams.

Customer issues are diagnosed faster and recur less often.

Engineering teams receive actionable feedback from production and customer pain.

Common operational problems become automated workflows, better diagnostics, clearer runbooks, or product fixes.

On-call pages trend toward roughly one per month.

The platform becomes easier to operate, easier to debug, and safer to change.

Customers experience fewer production surprises and faster resolution when issues do happen.