Platform Reliability Engineer

Bright Vision Technologies•Highlands Ranch, CO

1d•$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 increasing reliability and reducing operational toil. The engineer will use systems knowledge, programming skills, measurement-driven practices, automation, and disciplined service operations to make reliability a core engineering deliverable. This is a full-time, direct W2 position with Bright Vision Technologies, working remotely within the continental United States. The role supports the company’s in-house Statement of Work engagement; Bright Vision Technologies is the employer, with no third-party client, vendor, or implementation partner. The salary range is $135,000–$185,000. No new H1B sponsorship is available, but H1B transfers are supported for qualified candidates. A technical coding assessment is mandatory.

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.
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 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 as a full-time W2 employee of Bright Vision Technologies and contribute to in-house SOW deliverables.
A technical coding assessment is mandatory.
No new H1B sponsorship is available; qualified candidates currently on a valid H1B visa may apply for a transfer.

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 and refine SLOs, 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 tools such as Prometheus, Grafana, OpenTelemetry, ELK/EFK, Datadog, or similar tools.
Build and maintain on-call processes, runbooks, and escalation paths to improve detection and resolution times while protecting engineers’ well-being.
Automate operational toil by developing production-grade tooling in Python, Go, Bash, or similar languages.
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, with automated testing, canary deployments, feature flags, and progressive rollout strategies.
Lead capacity planning and performance engineering, develop growth and stress models, and validate them through load testing and chaos experiments.
Partner with application development teams to incorporate reliability practices into system 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.
Collaborate 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 in SRE practices and foster a blameless culture of operational excellence.