About the role
Company 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 Principal AI Engineer at TENEX, you will be a key technical leader responsible for designing, developing, and optimizing scalable, high-performance AI systems. You will play a crucial role in shaping the architecture of our AI-driven cybersecurity solutions while mentoring engineering teams and driving technical innovation. 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. Location: This role will require Monday - Thursday onsite in any of our locations. WFH Friday. Job
Responsibilities Design & build the AI layer that powers autonomous detection, RAG-backed investigation, and auto-remediation workflows. Develop and productionize large-scale LLMs, graph-based reasoning engines, and streaming feature pipelines that operate on billions of security events. Own evaluation & reliability —from prompt libraries and fine tuning to red-team testing, latency budgets, and fallback strategies. Mentor & grow a cohort of AI engineers; run design reviews, uphold code quality, and instill a security-first mindset. Partner tightly with Product, Detection Engineering, and Customer Success to translate real-world attacker behavior into robust ML and rule-based detections. Push the frontier —experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models (text + logs + graphs) to keep defenders decisively ahead. Required Skills &