SRE Operations Lead

SRE Operations LeadLocation: Charlotte, NC (onsite) Job Type: Full-Time Salary: $90,000 - $110,000 a yearWe are looking for an SRE Operations Lead to drive reliable, scalable, and automated production operations across AWS and GitLab environments. The role will focus on SRE operations, incident management, observability, DevSecOps, cloud automation, AIOps, and AI-assisted troubleshooting.The ideal candidate will have strong experience with AWS infrastructure, CI/CD, GitLab, Python/Shell scripting, observability platforms, incident response, and reliability engineering, along with the ability to leverage AI tools such as Claude and AWS Bedrock for troubleshooting and automation.Must Have Technical/Functional SkillsStrong experience in Site Reliability Engineering (SRE), Application Reliability Engineering (ARE). Strong knowledge of CI/CD, DevSecOps, production operations, incident management, and reliability engineering. Hands-on experience with AWS services, including: CloudWatch, Route 53, S3, CloudFront, ECR, EC2, Lambda, AWS Bedrock. Experience with GitLab repositories, CI/CD pipelines, branching strategies, and source-code management. Experience using AI-assisted development tools for troubleshooting, analysis, and automation. Strong Python and Shell/Bash scripting skills for operational automation and integration development. Experience with Grafana, Prometheus, CloudWatch, Splunk, Dynatrace, Datadog, OpenTelemetry, APM, and distributed observability. Strong understanding of SLIs, SLOs, SLAs, MTTR, reliability KPIs, service health, and operational resilience. Experience with incident management and P1/P2 major incident response, including root-cause analysis and service restoration. Experience implementing automation, AIOps, event correlation, self-healing, and AI-driven operations. Strong understanding of AWS containerized environments, Docker, Amazon ECR, and scalable cloud architectures. Experience with Terraform or similar Infrastructure as Code technologies. Experience developing and consuming REST APIs and integrating cloud, DevOps, and source-control platforms. Knowledge of GitLab APIs, Personal Access Tokens (PATs), custom workflows, and CI/CD automation. Experience with security scanning, vulnerability management, remediation, and DevSecOps controls. Knowledge of AWS Bedrock and AI-driven operational automation. Experience supporting resilient and multi-region AWS architectures. Strong troubleshooting, analytical, communication, and problem-solving skills.Roles & ResponsibilitiesSRE operations and coordinate P1/P2 major incident response through service restoration, root-cause analysis, and follow-up actions. Define and monitor SLIs, SLOs, SLAs, MTTR, availability, reliability, and operational performance KPIs. Drive end-to-end observability across applications and infrastructure using Grafana, Prometheus, CloudWatch, Splunk, Dynatrace, Datadog, and OpenTelemetry. Lead initiatives around AIOps, event correlation, self-healing, automated remediation, and AI-driven operations. Manage and optimize AWS platform operations, including compute, storage, networking, containers, serverless workloads, and deployment environments. Support AWS Lambda, ECR, EC2, S3, CloudWatch, CloudFront, Route 53, and Bedrock environments. Design and implement automation to improve operational efficiency, reliability, and incident response. Integrate AI tools with AWS Bedrock and GitLab using APIs, PATs, and custom automation workflows. Develop AI-assisted solutions for analyzing GitLab projects, vulnerabilities, pipelines, security findings, and operational data. Design and maintain GitLab API integrations, custom workflows, DevSecOps controls, and CI/CD improvements. Build and maintain Python-based GitLab integrations and REST API automation. Support vulnerability remediation and the onboarding, configuration, and maintenance of security scanning tools. Optimize AWS Lambda configurations, including concurrency, scaling, performance, and deployment automation. Design and support resilient multi-region AWS architectures and containerized deployments using Docker and Amazon ECR. Support batch-processing and scheduling environments, including Control-M where applicable. Partner with development, security, infrastructure, and application teams to improve system reliability and operational maturity. Identify recurring incidents and operational bottlenecks and implement permanent automation-based solutions. Establish operational standards, documentation, runbooks, monitoring strategies, and continuous improvement practices. Leverage AI and automation to reduce manual operational effort and improve troubleshooting, incident resolution, and service reliability.