DevOps Software Engineer

Software Engineer Mid-level (L4 equivalent) 2-5 years

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About the role

You will own the systems and practices that let engineers ship software safely and frequently, working at the intersection of development and operations. DevOps engineers here build the deployment pipelines, observability platforms, and reliability practices that the entire engineering organization depends on every day. You will automate away toil relentlessly, make deployments boring and routine, and lead incident response with calm precision when things go wrong. Your customers are your fellow engineers, and their productivity plus their confidence in the platform is your scorecard. Great DevOps work is invisible when it succeeds and invaluable when it prevents the outage nobody ever hears about.

What you will achieve

Build CI/CD pipelines that take code from commit to production safely: comprehensive automated tests, progressive rollouts, and one-click rollbacks
Deliver observability platforms with meaningful dashboards, actionable alerts, and distributed tracing that make debugging production issues fast
Reduce deployment lead time and change failure rate measurably through pipeline improvements tracked with DORA-style metrics over time
Lead incident response with clear coordination, genuinely blameless postmortems, and systemic fixes that prevent entire classes of future failures
Cut operational toil through aggressive automation: toil budgets, self-service tooling, and elimination of manual repetitive operational work

What you will bring

Must-haves

2 to 5 years in DevOps, SRE, or platform engineering roles with direct production systems responsibility
Strong CI/CD skills: designing pipelines in GitHub Actions, GitLab CI, Jenkins, or similar with proper testing and deployment stages
Experience with Kubernetes in production: deployments, networking, persistent storage, troubleshooting, and cluster operations
Familiarity with infrastructure as code using Terraform: module design, state management, and safe apply workflows with reviews
Knowledge of observability practices: Prometheus metrics, Grafana dashboards, log aggregation, and alert design that avoids fatigue
Scripting proficiency in Python or Bash for automation, operational tooling, and glue code between systems
BS in Computer Science or equivalent experience

Nice-to-haves

Experience with progressive delivery techniques: canary deployments, feature flags, and automated rollback strategies
Familiarity with service mesh technologies such as Istio or Linkerd for traffic management and security
Knowledge of chaos engineering practices and resilience validation performed safely in production
Experience with on-call program design: humane rotations, escalation policies, and burnout prevention