Description

Location: Tel Aviv

DriveNets is a leader in high-scale disaggregated networking solutions, modernizing how service providers, cloud providers, and hyperscalers build networks. Supporting the largest network in the world, more than half of AT&T’s backbone traffic runs on DriveNets’ Network Cloud architecture.

DriveNets is launching a new and exciting Cybersecurity business unit, focused on delivering advanced cyber solutions for Tier-1 Service Providers, leveraging DriveNets’ scale, performance, and cloud-native foundations.

The Role

We are looking for a Full-Stack Tech Lead to play a key role in building this new Cybersecurity unit from the ground up.

This is a highly impactful role for an engineer who can lead end-to-end development, own architecture, and turn advanced ideas into production-ready systems. The role combines hands-on full-stack development, technical leadership, and deep integration of LLM-based AI capabilities into cyber products.

Responsibilities

• Lead design and development of full-stack cyber security products, from frontend to backend.
• Own system architecture with focus on scale, performance, security, and reliability.
• Design and implement AI-powered capabilities using LLMs.
• Drive technical decisions and engineering best practices.
• Mentor and guide engineers through design and code reviews.
• Work closely with product and business stakeholders in a fast-growing unit.
  
  

Requirements

Must

BSc in Computer Science or related degree, or equivalent experience.

• 6+ years of experience as a Software Engineer.
• Proven experience as a technical leader / tech lead.
• Strong backend development experience (e.g., Python, Node.js, Java).
• Strong frontend development experience (e.g., React or similar).
• Experience designing APIs and distributed systems.
• Strong system design and problem-solving skills.
• Fast self-learner with strong ownership mindset.
  
  

AI & LLM Experience

• Deep understanding of LLMs, their behavior, limitations, and how to incorporate them into production systems.
• Experience with context engineering, prompt engineering, and retrieval-based workflows (e.g., RAG).
• Ability to design AI integration workflows and incorporate LLMs into larger application logic.
  
  

Advantage

• Experience with cloud-native architectures and CI/CD.
• Experience with databases and data pipelines.
• Experience working on high-scale, performance-critical systems.
• Experience developing high-scale security solutions.
• Experience with AI evaluation, guardrails, or cost optimization.