Role description
Staff Site Reliability Engineer
TENEX.AICompany Overview
TENEX is an AI-native, automation-first, built-for-scale Managed Detection and Response (MDR) provider. We are a force multiplier for defenders, helping organizations enhance their cybersecurity posture through advanced threat detection, rapid response, and continuous protection. Our team is composed of industry experts with deep experience in cybersecurity, automation, and AI-driven solutions. Backed by leading investors, we are rapidly growing and seeking top talent to join our mission of revolutionizing the AI-Native MDR landscape.
We’re a fast-growing startup backed by industry experts and top-tier investors led by Crosspoint Capital Partners and also backed by Shield Capital, DTCP (formerly Deutsche Telekom Capital Partners), Deepwork Capital, and the Florida Opportunity Fund. Seed round led by Andreessen Horowitz (a16z). As an early employee, you’ll play a meaningful role in defining and building our culture. Get in on the ground floor. We’re a small but well-funded team that just raised a substantial round – joining now comes with limited risk and unlimited upside.
As a Staff Site Reliability Engineer at TENEX, you will be a key technical driver responsible for ensuring the scalability, reliability, and performance of our AI-driven cybersecurity platform. You will play a crucial role in designing resilient infrastructure, automating operational workflows, and shaping the future of our production environments while collaborating across engineering teams to drive technical excellence.
Culture is one of the most important things at TENEX.AI—explore our culture deck at culture.tenex.ai to witness how we embody it, prioritizing the irreplaceable collaboration and community of in-person work.
You will Bring:
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.
Required Skills & Qualifications
SRE & Infrastructure Expertise
Core Engineering: 10+ years of experience in SRE, DevOps, or Software/Systems Engineering, particularly in managing production systems at scale.
Cloud Infrastructure: Deep expertise in public cloud environments (AWS, GCP, or Azure) and managing services such as Kubernetes (EKS/GKE), networking, and storage.
Infrastructure as Code: Extensive experience with tools like Terraform, Pulumi, or similar technologies to manage complex infrastructure deployments.
Observability: Hands-on experience with monitoring, logging, and tracing stacks (e.g., Prometheus, Grafana, ELK, Datadog) to drive data-informed reliability decisions.
Distributed Systems: Solid understanding of microservices architecture, distributed databases, and event-driven systems.
Soft Skills
Communication: Clear, concise communication skills and a bias for collaborative problem-solving.
Leadership Alignment: Proven track record of guiding multi-stakeholder initiatives and influencing engineering practices across teams.
Analytical Rigor: Strong problem-solving, debugging, and analytical skills, especially in high-pressure environments.
Nice-to-have
Domain Background: Prior work in cybersecurity, specifically regarding SIEM, EDR, or SOAR infrastructure.
AI/ML Infrastructure: Experience supporting infrastructure for large-scale AI/ML workloads (e.g., GPU scheduling, LLM serving optimization).
Startup Mentality: Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS.
Strong familiarity with Agentic Workflows such as Agno, Temporal, etc..
Education & Certifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Relevant certifications (CKA/CKAD, AWS/GCP Professional Cloud Architect, etc.) are a plus.
Why Join Us?
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.
If you're passionate about building resilient infrastructure, scaling AI systems, and working at the intersection of reliability and security, we encourage you to apply!