DevOps & SRE Engineer

Bright Vision Technologies
Fishers, IN, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$100,000 - $150,000
Working hours
Regular working hours

Tech stack

Java (Programming Language) Amazon Web Services Microsoft Azure Computer Programming Linux DevOps Distributed Systems Python (Programming Language) Load Testing Performance Tuning Reliability Engineering Prometheus
+7 more
Software Engineering Datadog Cloud Platform System Istio Grafana Kubernetes Linkerd (Service Mesh)

Job description

We are seeking an experienced DevOps & SRE Engineer to ensure the availability, performance, and operational excellence of large-scale distributed systems in production. As an SRE you will live at the boundary between development and operations, applying strong software engineering principles to infrastructure and operations problems, and continually pushing the platform toward higher reliability with lower operational toil. The ideal candidate will combine deep systems knowledge with strong programming skills, a measurement-driven mindset, and the discipline to design, automate, and operate complex services so that reliability becomes a first-class engineering deliverable rather than a reactive concern.

Requirements

  • More than 5 years of SRE, DevOps, or production engineering experience supporting large-scale distributed systems.
  • Strong programming skills in at least one of Python, Go, or Java, with the ability to build robust automation and tooling.
  • Deep, hands-on experience operating Linux at scale, including networking, performance tuning, and systems-level troubleshooting.
  • Production experience operating Kubernetes and container-based workloads.
  • Strong working knowledge of observability tooling such as Prometheus, Grafana, OpenTelemetry, ELK/EFK, or commercial equivalents.
  • Hands-on experience designing and operating CI/CD pipelines for both infrastructure and applications., * Experience defining and operationalizing SLOs and error budgets in real production environments.
  • Exposure to chaos engineering practices and tools such as Chaos Monkey, Gremlin, or Litmus.
  • Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
  • Background in capacity planning, performance engineering, or large-scale load testing.
  • Familiarity with service mesh technologies such as Istio, Linkerd, or Consul.

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