Senior Site Reliability Engineer

FidelityDurham, NC

About The Position

Our Site Reliability Engineering group within Enterprise Infrastructure combines Operations Excellence with the Development Experience to deliver services at high scale, high availability with resilience by using automation and Infrastructure Code. We build reliability into our ecosystem by applying best practices in Resiliency Engineering, Automation, Observability, Performance testing and Chaos testing. The team comes from diverse technical backgrounds, and the responsibilities provide the opportunity for a variety of challenges. Ideal candidates will have a background in either software engineering or systems engineering with a desire to learn the other or previous experience as an SRE. We are looking for a Systems Thinking, SRE Engineer who has helped teams scale through production insights, operational automation, developer guidance, real-time metrics, automation.

Requirements

  • Bachelor’s degree or higher in a technology related field (e.g. Engineering, Computer Science, etc.) required, master’s degree is a plus.
  • Minimum 5 years of hands-on experience deploying and/or supporting highly distributed multi-tiered systems at a scale.
  • 3 plus years of experience in Cloud development (AWS) and migration skills.
  • 3-5 years of experience in software development with Python, NodeJS, or Java with a focus on SDLC and automation.
  • Hands on experience with one or more observability tools (Datadog, Splunk, Kibana, Prometheus, Grafana, ELK/OpenSearch, Open Telemetry).
  • Hands on experience in designing, developing, and executing performance tests using K6/JMeter and other performance testing tools.
  • Hands-on experience with container orchestration, preferably with Kubernetes.
  • Strong knowledge of CI/CD pipelines and DevOps practices.
  • Strong programming/scripting skills in one or more: Python, Java, Go, or Bash.
  • Expertise in automation frameworks and tools for performance validation.
  • Experience managing systems using infrastructure as code tools (IAM, ARM, Terraform, Chef).
  • Solid understanding of Cloud Computing and DevOps concepts including CI/CD pipelines.
  • Experienced in Instrumentation with systems skills on building and operating, monitoring, logging, alerting services of distributed systems at scale.
  • Proven experience in maintaining scalability and resiliency of complex environments.
  • Proven experience in implementing advanced observability practices and techniques at scale.
  • Ability to triage, execute root cause analysis, and be decisive under pressure.
  • Experience managing and interpreting large datasets using query languages and visualization tools.
  • Proficient communication skills with an ability to reach both technical and non-technical audience.
  • Ability to work with a variety of individuals and groups, both in person and virtually, in a constructive and collaborative manner and build and maintain effective relationships.
  • Experience in design, implement, and maintain performance test frameworks, which will validate to a high degree of confidence, the production readiness of software applications and infrastructure for stability and performance.
  • Solid understanding of AWS services and experience setting up test environments on AWS (S3, EC2, RDS, etc.).

Nice To Haves

  • Master’s degree is a plus.
  • Familiarity with chaos engineering and resilience testing tools (e.g., Chaos Monkey, Gremlin).

Responsibilities

  • Deploying and/or supporting highly distributed multi-tiered systems at a scale.
  • Building and operating highly resilient platforms in AWS cloud environments.
  • Software development with Python, NodeJS, or Java with a focus on SDLC and automation.
  • Ensure platforms meet high availability, scalability, fault tolerance, and disaster recovery requirements.
  • Designing, developing, and executing performance tests using K6/JMeter and other performance testing tools to ensure comprehensive performance testing.
  • Define Performance Test Strategy Document: set approach, metrics, benchmarks, baseline, user response requirements environments, technical environment and data conditions, and toolsets to use in executing the performance testing.
  • Experience in performance testing types: Load testing, Stress testing, Scalability testing, Spike testing, Volume testing, Chaos testing, Endurance/Soak testing.
  • Container orchestration, preferably with Kubernetes.
  • Identifying memory leakage, connection issues and throughput bottlenecks in various technologies such as web application(s), infrastructure, and Cloud.
  • Working in high-availability, large-scale production environments.
  • Instrumentation with systems skills on building and operating, monitoring, logging, alerting services of distributed systems at scale.
  • Maintaining scalability and resiliency of complex environments.
  • Implementing advanced observability practices and techniques at scale.
  • Triage, execute root cause analysis, and be decisive under pressure.
  • Managing and interpreting large datasets using query languages and visualization tools.
  • Design, implement, and maintain performance test frameworks, which will validate to a high degree of confidence, the production readiness of software applications and infrastructure for stability and performance.
  • Setting up test environments on AWS (S3, EC2, RDS, etc.).
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