Build, ship, keep running.
3 AI translations · Technology / SaaS
Engineers write code, review PRs, refactor legacy systems, debug production issues, and maintain codebases that range from pristine monorepos to archeological dig sites. Code review is a bottleneck: senior engineers spend 20–40% of their time reviewing PRs, balancing thoroughness against velocity. Technical debt accumulates because refactoring loses to feature work in every sprint. Documentation is perpetually out of date because nobody writes it until onboarding a new engineer forces the issue.
Your SRE/on-call team manages production reliability: monitoring (Datadog, New Relic, PagerDuty, Grafana), incident response (detection, triage, mitigation, resolution, postmortem), SLO/SLI management, capacity planning, and chaos engineering. When the pager fires at 3am, you triage: is it a real incident or a false alarm? What's the blast radius? What's the most likely root cause? What's the fastest mitigation? You manage incident communication (StatusPage, Slack war rooms), coordinate across teams, and write postmortems. SLO attainment drives reliability investment decisions.
You maintain CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD): build, test, security scan, artifact creation, deployment, and release management. You manage deployment strategies (blue-green, canary, rolling, feature flags), rollback procedures, and release cadence. Pipeline reliability is critical — a flaky test suite slows everyone down. Security scanning (SAST, DAST, SCA, secret detection) is integrated into the pipeline but generates noise that needs triage. Release management for enterprise customers involves change management, release notes, and customer communication.