AI Engineer

Description Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world’s largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we're looking for people who want to be a part of the next rocket-ship in cyber. We're looking for an AI Engineer to join our team. As an AI Engineer at Vega, you’ll be a key member of our founding team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. You’ll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform. In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company. WHAT YOU WILL DO Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability. Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges. Own the full ML lifecycle — from ideation and experimentation to production readiness. Collaborate with product, engineering, and security teams to turn AI research into user-facing features. Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights. Evaluate and optimize AI system performance, scalability, and reliability. Contribute to core architectural decisions related to AI and ML infrastructure. Requirements WHAT YOU WILL BRING 4+ years of professional experience in ML/AI engineering. Hands-on experience working with LLMs and building AI agents in production environments. Strong understanding of text classification, ranking, and evaluation in NLP systems. Proficiency in Python and modern ML frameworks. Deep knowledge of deploying and maintaining AI systems at scale. Experience with cloud platforms, particularly AWS. Experience working independently in fast-paced, mission-driven environments Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field NICE TO HAVE Experience fine-tuning LLMs for domain-specific or task-specific use cases. Background in cybersecurity applications (e.g., threat detection, incident response, log analysis). Familiarity with agent-based architectures and autonomous systems.