Principal AI Engineer at TENEX designing and optimizing scalable AI systems for cybersecurity solutions and mentoring teams in a hybrid workplace.
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.
Requirements
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.
Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus.
Benefits
Competitive salary and benefits package
A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies
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