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 through advanced threat detection. The Principal AI Engineer will be responsible for designing and optimizing scalable AI systems, mentoring engineering teams, and driving technical innovation in AI-driven cybersecurity solutions.

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

Skills

• 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
• 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
• Strong problem-solving and analytical skills
• Excellent communication and leadership abilities
• Ability to mentor and influence engineering teams
• Passion for cybersecurity and automation
• 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

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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