Senior DevOps Engineer/Site Reliability Engineer-East Coast

Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market.. We are seeking a highly skilled Senior DevOps / Site Reliability Engineer (SRE) to join our globally distributed engineering organization. This is a hands-on senior-level role focused on building, operating, and scaling reliable cloud-native infrastructure and distributed data platforms. The ideal candidate will have strong expertise in Kubernetes, cloud infrastructure, observability, automation, CI/CD, incident management, and infrastructure reliability. This role combines DevOps engineering practices with SRE principles to improve scalability, resiliency, operational efficiency, and platform performance across production environments. The engineer will work closely with platform, development, and operations teams to drive automation, operational excellence, and reliability best practices for mission-critical systems. Key Responsibilities Administer and maintain Kubernetes clusters and containerized workloads. Manage cloud infrastructure across OCI, AWS, GCP, or Azure environments. Develop and maintain CI/CD pipelines for reliable application deployments. Implement and manage Infrastructure as Code (IaC) using Terraform and Helm. Build automation tooling and operational workflows using Python, Go, or Bash. Drive observability initiatives including monitoring, logging, tracing, and alerting improvements. Monitor, troubleshoot, and resolve production incidents while participating in on-call rotations. Support and optimize distributed data platforms including Kafka, Elasticsearch, Spark, Redis, and MongoDB. Improve platform reliability, scalability, and operational efficiency using SRE best practices. Collaborate with cross-functional teams across multiple time zones. Perform Linux system administration and networking troubleshooting. Contribute to incident response processes, postmortems, and reliability improvements. Support GitOps and deployment workflows using tools such as ArgoCD and GitHub Actions. Evaluate and implement AI-assisted operational tooling for auto-remediation, alert correlation, and operational intelligence. 5+ years of experience in DevOps, SRE, or Platform Engineering roles. Strong expertise with Kubernetes, Docker, and container orchestration. Hands-on experience managing production cloud environments. Strong Infrastructure as Code experience with Terraform and Helm. Experience with CI/CD tools and deployment automation. Advanced troubleshooting skills in Linux systems, networking, and distributed systems. Experience with observability platforms including Prometheus, Grafana, Loki, Alertmanager, and Elastic Stack. Strong programming and scripting skills in Python, Bash, or Go. Experience supporting high-availability production systems and on-call operations. Knowledge of incident management and reliability engineering practices. Familiarity with data platform technologies such as Kafka, Spark, Elasticsearch, Redis, or MongoDB. Understanding of AI-driven operational tooling and automated remediation concepts. Excellent communication, collaboration, and problem-solving skills. Resides on the East Coast We pride ourselves in recognizing our employees. Here are some examples of our benefits program: Pre-IPO Stock Options Medical, Dental & Vision care 401(k) Employee Assistance Program Employee Discount Program Life Insurance Paid time off Referral Program Rewards and Recognition Program The base compensation range for this role is USD 165,000-215,000 per year. Total compensation includes bonus opportunity and equity, and will vary based on candidate location.