tenex - AI Architect
Requirements
• 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. • 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. • 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.
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.
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