Site Reliability Engineer (SRE)

Bright Vision Technologies•Monroe Township, MI

13h•$100,000 - $180,000•Remote

About The Position

Bright Vision Technologies is seeking an experienced Site Reliability Engineer to ensure the availability, performance, and operational excellence of large-scale distributed systems in production. The role works at the boundary between development and operations, applying software engineering principles to infrastructure and operations while improving reliability and reducing operational toil. The position is 100% remote in the U.S., full-time, direct W2, with an annual salary range of $100,000–$180,000. It requires 10 or more years of relevant experience. The company cannot sponsor new H-1B visa petitions; U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply. The engineer will define and use reliability measures, lead incident response, build observability and automation, and operate Kubernetes-based platforms and CI/CD systems. The role also includes capacity and performance engineering, resilience and security improvements, collaboration with application teams, development of reliability tooling and practices, and mentoring engineers in a blameless culture. Bright Vision Technologies is an Equal Opportunity Employer and states that it prohibits discrimination and workplace harassment across all aspects of employment.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
Ten or more 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 tools such as Prometheus, Grafana, OpenTelemetry, ELK/EFK, or commercial equivalents.
Hands-on experience designing and operating CI/CD pipelines for infrastructure and applications.
Solid understanding of distributed system design, including consistency models, partitioning, and failure semantics.
Demonstrated experience leading incident response and conducting effective post-incident reviews.
Excellent communication and documentation skills.

Nice To Haves

Experience defining and operationalizing SLOs and error budgets in 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.

Responsibilities

Define, instrument, and refine SLOs, SLIs, and error budgets for critical services, using them to guide engineering and prioritization decisions.
Lead production incident response and resolution, serve as incident commander when needed, and conduct post-incident reviews that produce lasting improvements.
Design and implement monitoring, logging, and tracing strategies using tools such as Prometheus, Grafana, OpenTelemetry, ELK/EFK, and Datadog, or similar tools.
Build and maintain on-call processes, runbooks, and escalation paths to reduce detection and resolution times while protecting the well-being of engineers on rotation.
Automate operational toil by building production-grade tooling in Python, Go, Bash, or similar languages.
Architect and operate large-scale Kubernetes clusters and container workloads, including autoscaling, capacity planning, network policy, and service-mesh integration.
Design CI/CD pipelines for safe, frequent, observable releases, using automated testing, canary deployments, feature flags, and progressive rollout strategies.
Lead capacity planning and performance engineering, build growth and stress models, and validate them through load testing and chaos experiments.
Partner with application development teams to integrate reliability practices into design, including failure-mode analysis, graceful degradation, and dependency hardening.
Improve platform resilience through chaos engineering, fault injection, dependency isolation, retries, timeouts, circuit breakers, and tested failover paths.
Work with security teams to improve security posture, including patch management, vulnerability remediation, and secure-by-default platform settings.
Contribute to the technical roadmap for reliability tooling, observability platforms, and developer-experience improvements.
Mentor engineers on SRE practices and foster a blameless culture of operational excellence.