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TENEX.AI

AI Architect

Reposted 18 Days Ago
Remote
Hiring Remotely in USA
Senior level
Remote
Hiring Remotely in USA
Senior level
The AI Architect will define architecture for scalable AI systems, mentor engineers, and ensure operational excellence in cybersecurity solutions.
The summary above was generated by AI
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 an AI Architect at TENEX, you will be a key technical leader responsible for defining the architecture, design, and execution of our scalable, high-performance AI systems. You will play a crucial role in shaping the technical vision of our AI-driven cybersecurity solutions, ensuring they are reliable and scale to handle billions of security events. You will remain deeply hands-on, leading cross-functional design, making key technical decisions, and mentoring senior engineers.

Location: This role will require being onsite Monday - Thursday in our San Jose, CA, Sarasota FL or Kansas City, MO office. WFH on Friday.

Job Responsibilities

  • Set Technical Strategy & Vision: Oversee the design and architecture of scalable, reliable, and secure systems that power our autonomous detection, RAG-backed investigation, and auto-remediation workflows. Define the technical strategy and architecture for our core platform, ensuring it scales to petabytes of security data and billions of daily events.

  • Design & Build the AI Layer: Power 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: AI systems—from prompt libraries and fine tuning to red-team testing, latency budgets, and fallback strategies.

  • Own Operational Excellence & Reliability: Oversee cross-cutting concerns like observability, reliability, performance, security, and operational excellence in production environments operating on billions of security events.

  • Collaborate Cross-Functionally: Partner tightly with Product, Detection Engineering, and Customer Success to translate real-world attacker behavior into robust ML and rule-based detections, and define the technical roadmap, translating business needs into robust architectural requirements.

  • Foster Innovation: Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models (text + logs + graphs) to maintain a competitive advantage and keep our defenders decisively ahead.

  • Technical Mentorship: Mentor and influence engineering teams on best practices in cloud architecture, reliability, and security-first development.

Required Skills & Qualifications

Software Architecture & Systems Engineering

  • 10+ years of progressive experience in software development, with significant experience in a dedicated Software Architect or Principal Engineering role.

  • Deep technical expertise in designing and engineering scalable, distributed, and production-grade systems using modern programming languages (e.g., Python, Go, Rust, Java, or TypeScript).

  • Expertise in defining system architecture, microservices architecture, containerization (Docker, Kubernetes), and event-driven systems.

  • Strong fundamentals in API design (REST/gRPC), data modeling, and database technologies (SQL/NoSQL).

  • Experience with large-scale data processing, analytics, and high-volume transaction systems.

  • Extensive experience with cloud architecture (GCP, AWS, or Azure).

AI/ML Expertise

  • 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.

  • Hands-on experience with AI, LLM, and RAG architectures in a security-focused environment, including adversarial testing and mitigation of LLM hallucinations.

Nice-to-have

  • Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR) or a related domain/MSSP environment.

  • Experience with graph databases or security-focused knowledge graphs.

  • Familiarity with cloud infrastructure security (AWS, GCP, or Azure) and DevOps practices.

  • Experience leading engineering efforts for both backend services and complex single-page applications (SPAs) or data visualization tools.

  • Experience with large-scale data processing and stream processing (e.g., Kafka).

  • Background leading technical initiatives in high-growth startups or enterprise SaaS.

Soft Skills

  • Exceptional communication, presentation, and negotiation skills, with the ability to articulate technical strategy to executive leadership and external stakeholders.

  • Strong strategic thinking and analytical skills to solve complex business and technical problems.

  • Proven ability to mentor, inspire, and grow senior technical talent and leadership within the organization.

  • A strong passion for cybersecurity and a commitment to building security-first systems and automation.

  • Clear, concise communication skills and a bias for collaborative problem-solving.

Education & Certifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Relevant certifications (e.g., AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus.

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