Platform Reliability Engineer

Bright Vision Technologies•Sugar Land, TX

16h•$135,000 - $185,000•Remote

About The Position

Bright Vision Technologies is seeking an experienced Platform Reliability Engineer to ensure the availability, performance, and operational excellence of large-scale distributed systems in production. The role applies software engineering principles to infrastructure and operations, with a focus on improving reliability while reducing operational toil. The position is a full-time, direct W2 role supporting Bright Vision Technologies’ in-house Statement of Work engagement; the company is the employer, with no third-party client, vendor, or implementation partner. The role is 100% remote within the continental United States and offers a salary of $135,000–$185,000. A technical coding assessment is mandatory. No new H1B sponsorship is available, but qualified candidates needing an H1B transfer may apply.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
At least five 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, including 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.
Must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to its in-house SOW deliverables.
Must complete a technical coding assessment.
No new H1B sponsorship is available; qualified applicants requiring an H1B transfer are welcome to apply.

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 a major cloud platform such as 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 service-level objectives (SLOs), service-level indicators (SLIs), and error budgets for critical services, and use 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 drive lasting improvements.
Design and implement monitoring, logging, and tracing strategies using Prometheus, Grafana, OpenTelemetry, ELK/EFK, 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 on-call engineers.
Automate operational toil with production-grade tooling in Python, Go, Bash, or similar languages, replacing manual workflows with reliable, auditable automation.
Architect and operate large-scale Kubernetes clusters and container-based 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, create growth and stress models, and validate them through load testing and chaos experiments.
Partner with application development teams to incorporate reliability practices early in system design, including failure-mode analyses, graceful degradation, and dependency hardening.
Improve platform resilience using chaos engineering, fault injection, dependency isolation, retries, timeouts, circuit breakers, and tested failover paths.
Work with security teams to improve security posture through 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.