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# Principal Site Reliability Engineer (SRE)

- **Company:** Ally Financial Inc.
- **Location:** Charlotte, NC, United States (Remote available)
- **Experience:** Expert
- **Salary:** $110,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Systems Engineering, Computer Programming, Computer Networks, DevOps, Disaster Recovery, Distributed Systems, Domain Name System (DNS), Github, Monitoring of Systems, Python (Programming Language), Node.Js, Octopus Deploy, Reliability Engineering, Prometheus, Systems Integration, Datadog, Circleci, Pulumi, Load Balancing, Grafana, Reliability of Systems, Cloudformation, Kubernetes, Infrastructure Automation Frameworks, Deployment Automation, Production Code, Terraform, New Relic (SaaS), Dynatrace, Jenkins, Microservices
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1f93b4d556808334

## About the Role

* 7+ years of relevant experience
 * Bachelor's degree in relevant field(s) of study or equivalent, * 5+ years of experience in site reliability engineering, systems engineering, or DevOps roles with a proven track record of maintaining large-scale production systems
 * Deep expertise in cloud AWS including infrastructure as code tools like Terraform, CloudFormation, or Pulumi
 * Experience defining and measuring SLIs, SLOs, and error budgets, and using them to drive reliability improvements and inform product decisions
 * Proficiency in AI development
 * Strong programming skills in languages such as Python, Go, or Node with the ability to write production-quality code for automation, toolinQCg, and system integration
 * Extensive experience with container orchestration (ECS or similar) and microservices architectures in production environments
 * Proficiency with observability and monitoring tools such as: Dynatrace, Prometheus, Grafana, Datadog, New Relic, or similar and experience building comprehensive monitoring and alerting systems
 * Solid understanding of networking concepts, load balancing, CDNs, DNS, and distributed systems principles including consensus algorithms and failure modes
 * Hands-on experience with CI/CD pipelines and GitOps workflows using tools like Jenkins, GitHub Actions, ArgoCD, or CircleCI
 * Strong incident management and troubleshooting skills with the ability to quickly diagnose and resolve complex production issues under pressure
 * Excellent communication and collaboration skills with the ability to influence technical direction across multiple teams and mentor engineers at various levels

## Description

The Business Intelligence (BI) & Reporting Lead will play a pivotal role in transforming raw data into actionable insights that support our technology portfolio. This role is crucial for advancing our Generative AI and Machine Learning capabilities in reporting, ensuring that our product and technology PMO needs are met with innovative solutions.

The Work Itself

 * At Ally, you get a startup feel, but experience the benefits of a company that's worked out the kinks and is fulfilling its purpose. We're always evolving and see that as a good thing. From owning our work to seeing its impact in the real world, our team is relentless in finding new ways technology can help make experiences better and help people. We are problem solvers, we value diverse thinking, we support one another, and we challenge ourselves to think bigger in the journey to deliver customer-obsessed tech solutions.
At this time, Ally will not sponsor a new applicant for employment authorization for this position.

 * Design and implement highly available, scalable infrastructure systems that support mission-critical production services, including automated deployment pipelines, observability platforms, and disaster recovery
 * Lead incident response and postmortem processes, diving deep into complex distributed systems failures to identify root causes and drive systemic reliability improvements across engineering teams
 * Develop and maintain service level objectives (SLOs) and error budgets, using data-driven approaches to balance feature velocity with system reliability and guide organizational decision-making
 * Build tooling and automation to eliminate toil, improve operational efficiency, and enable engineering teams to safely deploy and operate services with minimal manual intervention