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 MDR landscape.
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.
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 finetuning 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 & Qualifications
Software Engineering & Architecture Expertise
10+ years of experience in software development, engineering production systems using modern programming languages (Python, Go, Rust, or Java).
Deep knowledge of
LLM architecture, prompt engineering, and Vector database
workflows.
Hands-on experience building
agents , orchestration frameworks (LangChain/LangGraph, Agno AGI, or custom), and evaluation harnesses.
Deep understanding of microservices architecture, containerization (Docker, Kubernetes), and event-driven systems.
Strong fundamentals in
API design
(REST/gRPC) and distributed systems.
Clear, concise
communication
skills and a bias for collaborative problem-solving.
Nice-to-have
Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR).
Experience with graph databases or security-focused knowledge graphs.
Familiarity with cloud infrastructure security (AWS, GCP, or Azure).
Background leading teams in high-growth startups or enterprise SaaS.
Soft Skills
Strong problem-solving and analytical skills.
Excellent communication and leadership abilities.
Ability to mentor and influence engineering teams.
Passion for cybersecurity and automation.
Education & Certifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus.