Tel Aviv · Hybrid | Full-Time | Cybersecurity
About DriveNets
DriveNets is redefining networking with a cloud-native, disaggregated approach that powers the world's largest service providers and hyperscalers. Our AI-era infrastructure enables carriers and enterprises to scale GPU clusters and AI workloads across distributed networks — faster, more efficiently, and at unprecedented scale.
The Role
We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power DriveNets' next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
• Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
• Architect and operate multi-agent systems in production — including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
• Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
• Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
• Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
• Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
• Establish best practices for model observability, safety, and responsible AI deployment within the organization
• Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption
Must-Have
• 5–8 years of software engineering experience, with at least 2–3 years focused on AI/ML engineering
• Hands-on experience building production-grade LLM applications — RAG, agents, tool use, or fine-tuning
• Proven experience designing and running multi-agent systems in production: orchestration patterns, agent state management, retries, and graceful degradation
• Experience monitoring and observing AI agents in production — execution tracing, latency tracking, failure detection, and alerting (e.g., LangSmith, Arize, custom observability stacks)
• Proficiency with agentic frameworks: LangChain, LangGraph, and/or AWS Bedrock AgentCore
• Strong Python skills and comfort working across the full AI application stack
• Experience designing and operating MLOps pipelines (model versioning, deployment, monitoring)
• Solid understanding of transformer-based models, embeddings, and vector databases (e.g., Pinecone, Weaviate, pgvector)
• Comfortable working in cloud environments (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes)
• Strong problem-solving skills and ability to work autonomously in a fast-paced environment
Nice-to-Have
• Background in cybersecurity — threat detection, SIEM, SOC automation, or security data analysis — a significant plus for this role
• Familiarity with networking concepts (SDN, cloud-native networking, BGP, telemetry)
• Experience with model evaluation and benchmarking (LLM-as-judge, RAGAS, or custom eval harnesses)
• Exposure to MCP (Model Context Protocol) for tool-augmented agentic workflows
• Prior experience in enterprise SaaS, networking, or telecom domains
• Publications, open-source contributions, or projects in the LLM/GenAI or agentic AI space
Our Stack
Python · PyTorch · OpenAI / Anthropic APIs · LangChain · LangGraph · AWS Bedrock AgentCore · LangSmith · Kubernetes · Kafka · Elasticsearch · AWS · PostgreSQL · GitHub · Jira · Confluence
Why Join Us
• Work on AI-powered cybersecurity for the networks that carry global internet traffic
• Build and own production multi-agent systems — real scale, real impact
• Greenfield AI team within Cybersecurity — you will shape how AI is built and deployed at DriveNets
• Competitive salary, equity, and benefits
• Flexible hybrid model from our Tel Aviv office
• A culture of ownership, speed, and engineering excellence
DriveNets is a rapidly growing software company that has created a radical new way for service providers and hyperscalers to build their networking infrastructure. DriveNets Network Cloud and DriveNets Network Cloud-AI are new innovative networking solutions that apply the cloud architectural approach to high-scale networking. They bring together the scalability of standard Ethernet Clos architecture with the high performance and reliability of service provider networking, delivering optimal networking performance, scale and cost structure for service providers and hyperscalers.
Founded by Ido Susan and Hillel Kobrinsky, two successful telco entrepreneurs, DriveNets Network Cloud is the leading open disaggregated networking solution based on cloud-native software running over standard white boxes.
Over three funding rounds, DriveNets raised $587 million. Its solutions are used by tens of service providers globally and are in proof-of-concept and lab trials at dozens of operators and hyperscalers, consistently ranking #1 in trials for breadth of capabilities and solution quality. AT&T, the largest backbone in the US, deployed DriveNets Network Cloud across its core network, and DriveNets is currently transporting more than 52% of AT&T’s core network traffic. DriveNets is engaged with over 100 Tier-1 operators and cloud-providers on large projects in North America, Asia and Europe.
