Key skills
Site Reliability Engineering (SRE)DevOpsSystems EngineeringAWSGoogle Cloud Platform (GCP)Microsoft AzureKubernetes (EKS/GKE)StorageTerraformPulumiPrometheusGrafanaELK StackDatadogMicroservices ArchitectureDistributed DatabasesEvent-Driven SystemsCybersecuritySIEMEDRSOARAI/ML InfrastructureGPU SchedulingLarge Language Model (LLM) Serving OptimizationAgentic Workflows AgnoAgentic Workflows TemporalCertified Kubernetes Administrator (CKA)Certified Kubernetes Application Developer (CKAD)AWS Professional Cloud ArchitectGCP Professional Cloud ArchitectAIMLLLMAgenticAzureGCPKubernetesEKSGKESaaSCommunication
About this role
TENEX.AI is an AI-native, automation-first Managed Detection and Response provider seeking a Staff Site Reliability Engineer. In this role, you will ensure the scalability, reliability, and performance of their AI-driven cybersecurity platform by designing resilient infrastructure and automating operational workflows.
Responsibilities:
- Design, build, and maintain highly available, scalable, and secure infrastructure to support our AI-native cybersecurity platform
- Develop internal tooling and automation to streamline deployment processes, incident response, and capacity planning
- Monitor system performance and proactively identify bottlenecks, optimizing infrastructure for low-latency, high-throughput AI workloads
- Lead incident response efforts, conduct post-mortems, and implement long-term solutions to prevent recurring reliability issues
- Manage infrastructure via code, driving consistency, auditability, and scalability across our cloud environments (e.g., AWS, GCP)
- Partner with sibling Engineering teams, Product, and Security teams to ensure reliability is baked into our development lifecycle from concept to production
Requirements:
- 10+ years of experience in SRE, DevOps, or Software/Systems Engineering, particularly in managing production systems at scale
- Deep expertise in public cloud environments (AWS, GCP, or Azure) and managing services such as Kubernetes (EKS/GKE), networking, and storage
- Extensive experience with tools like Terraform, Pulumi, or similar technologies to manage complex infrastructure deployments
- Hands-on experience with monitoring, logging, and tracing stacks (e.g., Prometheus, Grafana, ELK, Datadog) to drive data-informed reliability decisions
- Solid understanding of microservices architecture, distributed databases, and event-driven systems
- Clear, concise communication skills and a bias for collaborative problem-solving
- Proven track record of guiding multi-stakeholder initiatives and influencing engineering practices across teams
- Strong problem-solving, debugging, and analytical skills, especially in high-pressure environments
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Prior work in cybersecurity, specifically regarding SIEM, EDR, or SOAR infrastructure
- Experience supporting infrastructure for large-scale AI/ML workloads (e.g., GPU scheduling, LLM serving optimization)
- Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS
- Strong familiarity with Agentic Workflows such as Agno, Temporal, etc