Systems Operations Engineer

Location: Charlotte, NC

Salary: $61.00 USD Hourly - $66.00 USD Hourly

Description:

Job Title: Senior Site Reliability Engineer (Systems Operations Engineer)

Location: Charlotte, NC or Irving, TX

Schedule: Hybrid - 3 days per week onsite (mandatory)

Contract: 18 months (with possible extension and eligibility for conversion)

About The Role

We are seeking a highly skilled Senior Site Reliability Engineer (SRE) to support key Shared Services Operations Technology platforms, including Payment Evaluations, Regulatory Operations, Financial Crimes, and Business & Real Estate Evaluation. You will be part of a team responsible for maintaining availability, performance, and reliability across ~85 applications that support KYC, AML, and other critical financial-crimes-related workloads.

This role blends software engineering, systems operations, and cloud-native reliability practices to drive automation, enhance resilience, and support modernization across a large enterprise ecosystem. You will also help evolve AIOps capabilities, including predictive alerting, self-healing workflows, and AI/ML-driven incident analysis.

Some occasional weekend work or overtime may be required for critical system support.

What You'll Do

Site Reliability & Operations

• Lead SRE practices that enhance system availability, performance, and scalability across multi-cloud environments.
• Support and improve critical applications and customer journeys; lead incident response and blameless postmortems.
• Conduct root-cause analysis and drive long-term remediation of recurrent issues.
• Define and enforce operational readiness and Non-Functional Requirements (NFRs) during platform modernization.
  
  

Automation & Tooling

• Design and implement automation to eliminate operational toil and improve service reliability.
• Build frameworks for automated SLO/SLI tracking, availability metrics, error budgeting, and customer impact analysis.
• Implement self-healing and autonomic systems using AI/ML, RPA, and intelligent monitoring.
  
  

Monitoring, Observability & AIOps

• Develop and enhance monitoring, alerting, and observability capabilities.
• Drive adoption of AIOps platforms to support anomaly detection, predictive alerting, and automated incident resolution.
  
  

Collaboration & Leadership

• Collaborate with platform teams, product owners, and technology partners across the COO Technology organization.
• Mentor peers and champion SRE best practices across engineering teams.
• Identify process gaps across domains and recommend scalable, long-term improvements.
  
  

Required Qualifications

• 5 years in Systems Engineering, Site Reliability Engineering, Technology Architecture, or related fields (or equivalent military/training/education experience).
• 2 years performing as part of an SRE team.
• Strong written and verbal communication skills.
  
  

Technical Skills

Software Development

• Proficiency in Python and/or Java/J2EE.
• Experience with REST APIs, microservices, Kafka/MQ, and modern integration patterns.
• Familiarity with JavaScript frameworks (React, Bootstrap).
• Strong SQL skills and database schema design experience.
  
  

Infrastructure & Cloud

• Expertise with Linux and container orchestration (Kubernetes, OpenShift/OCP strongly preferred).
• Experience with PCF, AWS, Google Cloud Platform, or Azure environments.
  
  

CI/CD & Automation

• Tools: Jenkins, GitLab, SonarQube, Artifactory, Ansible.
  
  

Observability & AIOps

• Tools: Grafana, Prometheus, Splunk/ELK, AppDynamics, Elastic, ThousandEyes, Aternity, Google Cloud Logging.
• AIOps Platforms: Moogsoft, AI/ML-based analytics frameworks.
  
  

Operations & Data

• ITSM Tools: ServiceNow, Remedy, IBM Netcool.
• Databases: Oracle, DB2, SQL Server, MongoDB, Hadoop/Cloudera, Spark, Teradata.
  
  

Foundational AI Knowledge

• Understanding of common AI/ML concepts (classification, regression, clustering, anomaly detection).
• Ability to work with structured/unstructured data for model evaluation.
• Awareness of ethical/operational considerations in AI systems.
• Experience integrating AI into automation workflows is a plus.
  
  

Preferred Qualifications

• Experience with AutoSys.
• Prior experience in corporate banking or financial services.
• Strong interest in AI-driven operations and AIOps.
  
  

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Contact:

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