A startup company developing a cybersecurity product in the Identity space, combining the worlds of LLM and Security. The product they’re building is essentially an LLM Agent that introduces a completely new way for organizations to manage identity internally enabling natural language interactions between employees and internal systems to handle identity processes that, until now, couldn’t be executed in such a way.

These are agentic systems, considered by many to be the modern way to build information systems in the near future.

The company is at the forefront of this rapidly evolving field, building a network of agents capable of autonomously addressing security (and other) events within large organizations.

Based in Tel Aviv, with a hybrid model that includes one day of remote work per week.

The company currently has 22 employees and is in a phase of rapid growth following a $16M funding round.

About the Role:

• Join a growing team focused on building advanced Data infrastructure using Python
• Design and implement data modeling and data optimization pipelines
• Architect scalable, real-time data systems to support LLM and ML workflows
• Collaborate with Data Scientists to integrate and optimize machine learning and LLM-driven workflows
• Support real-time RAG pipelines and ML-powered features through robust data architecture

Requirements-

• 5+ years of experience in backend and data engineering
• Proven ability to design and build large-scale cloud-based data architectures from scratch
• Hands-on experience with complex backend systems and high-performance data processing
• Strong background in data modeling for both real-time and batch processing
• Experience with streaming data technologies (e.g., Kafka, Pub/Sub)
• Deep knowledge of modern databases: SQL, NoSQL, Graph, NewSQL, with focus on performance optimization
• Familiarity with data security, encryption, and governance best practices
• Commitment to code quality, automated testing, and CI/CD practices