Lead Infrastructure Engineer, SRE

Corelight

full-time

Posted on: 9/24/2025

Origin: • 🇺🇸 United States

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Salary

💰 $184,000 - $229,000 per year

Job Level

Senior

Tech Stack

AnsibleApacheAWSCloudDistributed SystemsDockerElasticSearchGoKafkaKubernetesPythonSparkSplunkTerraform

About the role

Collaborate with development and quality engineering to build and maintain the continuous integration pipeline from development to production.
Engage in overall software architecture from design to implementation, monitoring, and testing.
Drive Corelight SaaS Cloud architecture, working closely with Engineering, Product, and other technical leaders.
Drive SaaS Operations improvements including Cost, Monitoring, Security, Change Management controls, etc.
Design, develop and maintain robust and scalable Machine Learning pipelines Infrastructure.
Implement automation, disaster recovery, and system resilience best practices.
Work in an Agile development team to design and deliver service features end-to-end from design to production deployment and monitoring.
Engage in hands-on, in-depth analysis, review, and design of the Cloud Infrastructure, high availability, resilience, and meeting stringent SLO objectives.
Work closely with offshore teams on various development projects.

Requirements

10+ years of Enterprise Distributed System Architecture, Public Cloud Infrastructure, Observability, and Infrastructure as a Code.
Experience programming skills in Python or Golang.
Experience with Infrastructure as code (Terraform, Pulumi) and Ansible.
Hands-on experience with Kubernetes, Kafka, Elastic Search, Docker, and Containers.
Experience with CI/CD practices, pipelines, monitoring and alerting tools, and automated test suite frameworks such as Gitlab, cloud devops tools, etc.
Experience with current SRE/DevOps best practices.
Experience in architecting, building, and scaling platforms and distributed systems that require high availability, resilience, and meeting stringent SLO objectives.
Knowledgeable in distributed systems and redundancy / high-availability and performance optimizations.
Experience in designing and implementing infrastructure for machine learning pipelines using Apache Spark or Apache Flink.
Solid understanding of distributed systems and big data technologies.
Familiarity with AWS, particularly Lambda, APIGW, MSK, EMR, AppSync, EKS, MLOps.
Experience in optimizing and troubleshooting complex, managing/deploying large-scale cloud infrastructure (preferred).
Experience in backup strategies and Disaster Recovery (preferred).
Knowledge of Network-based Security Detections and Attack techniques desirable (preferred).
Experience with Search and Analytics tools like Splunk, Elasticsearch (preferred).
Experience working in a distributed team (preferred).
Good to have compliance requirements of FedRAMP, GDPR, SOC2, etc. (preferred).
Familiar with security and risk mitigation (authentication, encryption, anomaly detection) for a cloud-based environment.