> Markdown version of [/jobs/ext/3754709-infrastructure-site-reliability-engineer-sre-train-ai-models-part-time](https://www.wearedevelopers.com/jobs/ext/3754709-infrastructure-site-reliability-engineer-sre-train-ai-models-part-time). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure / Site Reliability Engineer (SRE) (Train AI Models Part Time - **Company:** Mercor, Inc. - **Location:** United States - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Bash Shell, Cloud Computing, Cloud Engineering, Computer Programming, Continuous Integration, Software Debugging, Linux, DevOps, Distributed Systems, Python (Programming Language), Reliability Engineering, Prometheus, Software Deployment, Software Engineering, Datadog, Data Logging, Pulumi, Scripting, Cloud Platform System, Grafana, Reliability of Systems, Kubernetes, Terraform - **Published:** October 15, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3021307801-2 ## About the Role Professional experience in Infrastructure Engineering, Site Reliability Engineering (SRE), Platform Engineering, DevOps, or Production Engineering . - Hands-on experience operating complex, enterprise-grade production systems . - Strong production experience with Kubernetes . - Strong experience with AWS and cloud-native infrastructure. - Experience with Datadog , Prometheus, Grafana, or comparable observability platforms. - Experience with Infrastructure as Code using Terraform, Pulumi, or equivalent technologies . - Strong understanding of distributed systems, networking, containers, Linux, and cloud architecture. - Experience building or maintaining CI/CD and production deployment infrastructure. - Strong debugging, troubleshooting, and incident-response capabilities. - Proficiency in at least one programming or scripting language, such as Python, Go, or Bash . Strong Signals - Experience operating Kubernetes and cloud infrastructure at significant production scale. - Experience supporting high-traffic or mission-critical applications. - Experience building infrastructure or platform tooling used by large engineering organisations. - Ownership of production reliability, on-call operations, incident response, or capacity planning. - Experience working within sophisticated, large-scale distributed systems. - Demonstrated improvements to SLOs/SLIs, observability, deployment reliability, infrastructure performance, or operational efficiency . Why Join - Solve challenging reliability, scalability, and performance problems across enterprise-grade production systems. ## Description Mercor connects exceptional technical talent with leading organisations working on ambitious technology and AI initiatives. We are looking for experienced Infrastructure / Site Reliability Engineers (SREs) to join a full-time engagement focused on building and operating complex, enterprise-grade infrastructure. We are seeking engineers with strong hands-on experience building, operating, debugging, and scaling sophisticated production systems. The ideal candidate has worked extensively with Kubernetes, AWS, observability platforms such as Datadog, and modern infrastructure tooling . This is a full-time opportunity , and candidates must be able to commit to full-time engagement. What You'll Do - Build, operate, and improve highly available and scalable production infrastructure. - Manage and optimise Kubernetes-based production environments . - Design and maintain cloud infrastructure, primarily across AWS . - Improve system reliability, availability, scalability, and operational efficiency. - Build and maintain observability across infrastructure and applications using Datadog or similar platforms. - Investigate production incidents, perform root-cause analysis, and implement durable fixes. - Improve monitoring, alerting, logging, tracing, and overall production visibility. - Develop automation and internal tooling to reduce manual operational work. - Partner closely with software engineering teams on deployments, infrastructure, and production reliability. - Contribute to infrastructure architecture and technical decisions for complex distributed systems.