Senior Site Reliability Engineer

Wonder Group•Chicago, NY

6d•Hybrid

About The Position

As a Senior Engineer on the Runtime Automation team, you will design, automate, and secure our core infrastructure, deployment platforms, and CI/CD ecosystems. Our team is responsible for managing our centralized Enterprise Logging Platform (Vector, Datadog, Splunk), engineering robust multi-cloud solutions across AWS and GCP, and driving automated deployment infrastructure via Jenkins and Spinnaker. In this role, you will focus deeply on containerization (Docker), Infrastructure as Code (IaC via Terraform and/or Pulumi), server image management (AMI), and low-level Linux operating system engineering, while ensuring top-tier observability and strict security across our mission-critical card payment environment. This is a high-impact position driving continuous reliability, deep system optimization, and automation across our entire technology ecosystem.

Requirements

Technical Leadership and Mentorship: Proven experience or strong aptitude for helping guide technical direction, making sound architectural choices, and successfully coaching/mentoring other engineers.
Infrastructure as Code (IaC) Expertise: Hands-on familiarity and engineering experience with modern IaC frameworks, specifically Terraform and/or Pulumi, to manage complex cloud resources.
CI/CD and Deployment Expertise: Robust, hands-on familiarity with configuring, scaling, and troubleshooting enterprise CI/CD systems, specifically Jenkins pipelines and Spinnaker deployments.
Linux Internals and Systems Engineering: Deep, expert-level proficiency in Linux operating systems with proven experience in low-level system performance troubleshooting.
Automation and Advanced Scripting: High proficiency in scripting and software automation utilizing Python and Bash to build internal tools, optimize processes, and eliminate technical overhead.
Core Cloud Expertise: Strong engineering experience with AWS services (specifically EC2, Load Balancers, and AMI building) along with robust operational familiarity with Google Cloud Platform (GCP).
Containerization and Image Automation: Advanced, hands-on experience with Docker containerization and automated configuration management tools (such as Ansible).
Observability and Logging Expertise: Solid command over administering, configuring, and scaling large-scale enterprise logging and monitoring solutions, specifically Vector, Datadog, and Splunk.
Security-First Mindset: Strong familiarity with building and maintaining secure infrastructure, particularly within highly regulated or card payment environments.
Collaboration and Communication: Excellent problem-solving skills, rigorous attention to detail, and a proven ability to lead cross-functional incident responses and knowledge sharing.

Nice To Haves

Prior exposure to or experience with Kubernetes-native orchestration and architectures (e.g., EKS, GKE).

Responsibilities

Guide Technical Direction and Innovation: help define architectural strategies, introducing modern platform engineering practices, and driving complex technical decisions across infrastructure and CI/CD platforms.
Coach and Mentor Engineers: Foster a culture of technical excellence by mentoring and coaching mid-level and junior engineers, conducting rigorous code and architecture reviews, and promoting continuous knowledge sharing.
Scale Infrastructure as Code (IaC): Architect, maintain, and modernize declarative infrastructure across cloud environments using Terraform and/or Pulumi to drive reliability and self-service capabilities.
Orchestrate Global CI/CD Infrastructure: Own, scale, and optimize high-throughput multi-cloud deployment pipelines using Jenkins and Spinnaker, ensuring fast, secure, and friction-free software delivery workflows.
Secure and Standardize Payment Environments: Architect and harden our card payment infrastructure, ensuring the highest standards of data security, compliance, and proactive vulnerability mitigation.
Optimize Infrastructure and Container Lifecycles: Own and scale the automated pipeline for AWS AMIs and Docker containers, using configuration management tools to ensure consistent, secure, and reliable image deployment workflows.
Optimize Systems: Troubleshoot and optimize mission-critical infrastructure at scale, leveraging deep Linux internals knowledge and kernel-level tuning to maximize efficiency and stability.
Advance Enterprise Logging and Observability: Scale and maintain our data ingestion workflows and centralized logging platform using Vector, Datadog, and Splunk, building robust dashboards and advanced alerting mechanisms to minimize downtime.
Foster Operational Excellence: Participate in the team’s on-call rotation as an incident responder, leading postmortem discussions and writing automation scripts to eliminate repetitive operational toil.