Note: The job is a remote job and is open to candidates in USA. TENEX.AI is an AI-native, automation-first Managed Detection and Response provider focused on enhancing cybersecurity posture through advanced threat detection. As a Staff Site Reliability Engineer, you will ensure the scalability, reliability, and performance of the AI-driven cybersecurity platform by designing resilient infrastructure and automating operational workflows.
Responsibilities
- System Resilience: Design, build, and maintain highly available, scalable, and secure infrastructure to support our AI-native cybersecurity platform
- Automation & Tooling: Develop internal tooling and automation to streamline deployment processes, incident response, and capacity planning
- Performance Engineering: Monitor system performance and proactively identify bottlenecks, optimizing infrastructure for low-latency, high-throughput AI workloads
- Incident Management: Lead incident response efforts, conduct post-mortems, and implement long-term solutions to prevent recurring reliability issues
- Infrastructure as Code (IaC): Manage infrastructure via code, driving consistency, auditability, and scalability across our cloud environments (e.g., AWS, GCP)
- Cross-Functional Collaboration: Partner with sibling Engineering teams, Product, and Security teams to ensure reliability is baked into our development lifecycle from concept to production
Skills
- 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
- Relevant certifications (CKA/CKAD, AWS/GCP Professional Cloud Architect, etc.) are a plus
Benefits
- Opportunity to work with cutting-edge AI-driven cybersecurity technologies and Google SecOps solutions.
- Collaborate with a talented and innovative team focused on continuously improving security operations and system reliability.
- Competitive salary and benefits package.
- A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.
Company Overview