Staff Site Reliability Engineer

Jobtailor

Town of Florida (NY)

On-site

USD 180,000 - 240,000

Full time

4 days ago

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Job summary

Jobtailor is seeking an experienced Platform Architect/Lead to shape major cloud platform decisions and drive reliability across enterprise-scale workloads. You will own design, implementation, and ongoing improvements for critical systems, with heavy emphasis on observability and incident response.

You will lead capacity planning, performance tuning, and security enhancements while guiding on-call readiness and cross-functional collaboration.

Qualifications

5+ years of experience in Cloud Architecture, Site Reliability Engineering, Platform Engineering, or related fields.
Proven track record of designing and delivering at enterprise scale.
Deep, hands-on expertise with Google Cloud Platform (GCP) and Kubernetes (K8s).
Experience running high-volume, high-availability workloads with 99.999% reliability targets.
Expert-level command of monitoring, observability, and alerting platforms such as Datadog, Prometheus, Grafana, and PagerDuty.
Deep Linux expertise, including kernel internals, system performance tuning, hardening, and production OS troubleshooting.
Hands-on experience designing and integrating AI/ML-powered solutions into cloud-native platforms.
Familiarity with LLM orchestration, vector databases, model serving infrastructure, and AI observability.
Ability to evaluate emerging tools and translate them into reliable, production-grade capabilities.

Responsibilities

Contribute to architectural and strategic decisions around major platform components.
Lead research, testing, implementation, and continuous improvement for new systems and tooling.
Perform capacity planning, load testing, and security improvements.
Participate fully in the team’s on-call rotation.
Model calm, effective, and blameless incident response.
Serve as a significant technical contributor during major incidents and problem resolution.
Plan and lead high-risk maintenance events with minimal to no customer impact.
Elevate team standards through new tooling, processes, procedures, and effective communication.
Lead and represent the team during transitions or coverage gaps.
Set professional benchmarks in technical quality, engineering culture, and cross-functional collaboration.
Report to a DevOps Director

Skills

Cloud Architecture

Site Reliability Engineering

Google Cloud Platform

Kubernetes

Monitoring & Observability

Linux Expertise

AI/ML Integration

LLM Orchestration

Capacity Planning

Load Testing

Security Improvements

High-Availability Workloads

Tools

Datadog

Prometheus

Grafana

PagerDuty

Job description

Contribute to architectural and strategic decisions around major platform components
Lead research, testing, implementation, and continuous improvement for new systems and tooling
Perform capacity planning, load testing, and security improvements
Participate fully in the team’s on-call rotation
Model calm, effective, and blameless incident response
Serve as a significant technical contributor during major incidents and problem resolution
Plan and lead high-risk maintenance events with minimal to no customer impact
Elevate team standards through new tooling, processes, procedures, and effective communication
Lead and represent the team during transitions or coverage gaps
Set professional benchmarks in technical quality, engineering culture, and cross-functional collaboration
Report to a DevOps Director

Requirements

5+ years of experience in Cloud Architecture, Site Reliability Engineering, Platform Engineering, or related fields
Proven track record of designing and delivering at enterprise scale
Deep, hands-on expertise with Google Cloud Platform (GCP) and Kubernetes (K8s)
Experience running high-volume, high-availability workloads with 99.999% reliability targets
Expert-level command of monitoring, observability, and alerting platforms such as Datadog, Prometheus, Grafana, and PagerDuty
Deep Linux expertise, including kernel internals, system performance tuning, hardening, and production OS troubleshooting
Hands-on experience designing and integrating AI/ML-powered solutions into cloud-native platforms
Familiarity with LLM orchestration, vector databases, model serving infrastructure, and AI observability
Ability to evaluate emerging tools and translate them into reliable, production-grade capabilities

Core Competencies

Demonstrates extensive expertise in Cloud Architecture and Site Reliability Engineering, with a strong focus on Google Cloud Platform and Kubernetes. Proven ability to design and implement high-availability systems while leading incident response and continuous improvement initiatives.

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